CELL-SURFACE GLYCAN-LECTIN INTERACTIONS
FOR BIOMEDICAL APPLICATIONS
by
Maria Carolina Rodriguez Benavente
A Dissertation Submitted to the Faculty of
The Charles E. Schmidt College of Science in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy
Florida Atlantic University
Boca Raton, FL
May 2015
Copyright 2015 by Maria Carolina Rodriguez Benavente
ii
ACKNOWLEDGEMENTS
“Self-made people don’t exist. Anyone who has enjoyed success in the life is able to do so
because they have been helped by others. And I can tell you that when it comes to the massive
turnaround that my life has taken, it has not been a solo journey.”
- From “Growing Into Grace” by Mastin Kipp.
I am not a one-woman show. Any success I have had in life, is a result of numerous people who have supported me along the way. To my mentor, Dr. Predrag Cudic, thank you for allowing me the opportunity to grow as a research professional in your lab. I would like to thank my
Graduate Committee Members, Dr. Salvatore Lepore, Dr. Adel Nefzi, and Dr. Lyndon West, for all of your support, guidance, advice, and encouragement throughout my graduate degree. To my other mentor, Dr. Mare Cudic, thank you for believing in me.
One of the most gratifying experiences I have had along my graduate years was working at
The Torrey Pines Institute for Molecular Studies. Dr. Richard Houghten, thank you for making me a part of the TPIMS family. To all the faculty and staff at the Institute, your support has never gotten unnoticed, and I for one will never forget it. To the friends and colleagues I met at the
Institute, specially Dr. Ania Knapinska, Dr. Sabrina Amar, Ginamarie Debevec, and Laura Maida.
It has been an honor and a pleasure working and growing alongside with you. They say you are as special as the people you surround yourself with. Well, in that case, I am blessed.
Most importantly, to my family. If there was ever any unconditional support I received, was from you. Thank you for believing in me even when I was uncertain. Thank you for being my cornerstone of love and reassurance, especially at times when it felt strenuous and exhausting to continue. I made it through because of you, mom and dad. Thank you.
iv ABSTRACT
Author: Maria Carolina Rodriguez Benavente
Title: Cell-Surface Glycan-Lectin Interactions for Biomedical Applications
Institution: Florida Atlantic University
Dissertation Co-advisors: Dr. Salvatore D. Lepore Dr. Predrag Cudic
Degree: Doctor of Philosophy
Year: 2015
Carbohydrate recognition is one of the most sophisticated recognition processes in biological systems, mediating many important aspects of cell-cell recognition, such as inflammation, cell differentiation, and metastasis. Consequently, lectin-glycan interactions have been intensively studied in order to mimic their actions for potential bioanalytical and biomedical applications.
Galectins, a class of ß-galactoside-specific animal lectins, have been strongly implicated in inflammation and cancer. Galectin-3 is involved in carbohydrate-mediated metastatic cell heterotypic and homotypic adhesion via interaction with Thomsen-Friedenreich (TF) antigen on cancer-associated MUC1. However, the precise mechanism by which galectin-3 recognizes TF antigen is poorly understood. Our thermodynamic studies have shown that the presentation of the carbohydrate ligand by MUC1-based peptide scaffolds can have a major impact on recognition, and may facilitate the design of more potent and specific galectin-3 inhibitors that can be used as novel chemical tools in dissecting the precise role of galectin-3 in cancer and inflammatory diseases. Another lectin, odorranalectin (OL), has been recently identified from Odorrana grahami skin secretions as the smallest cyclic peptide lectin, has a particular selectivity for L-fucose and very low toxicity and immunogenicity, rendering OL an excellent candidate for drug delivery to targeted sites, such as: (1) tumor-associated fucosylated antigens implicated in the pathogenesis of several cancers, for overcoming the nonspecificity of most anticancer agents; (2) the olfactory
v epithelium of nasal mucosa for enhanced delivery of peptide-based drugs to the brain. Described in this dissertation is a simple and robust approach toward the solid-phase synthesis of OL and its analogs, based on standard Fmoc-solid phase peptide synthesis protocols. Lectin-cell staining studies reveal preferential binding towards cancer cell lines that overexpress fucosylated antigens on their cell surface when compared to healthy cells. In addition, our in vivo mice studies show fast intranasal delivery of OL to mouse brain in amounts detectable by mass spectrometry, thus offering a novel brain drug delivery system for the treatment of central nervous system (CNS) disorders. Altogether, the research described in this dissertation demonstrates that new ‘lectin- mimicking’ peptides related to lectins or their target glycans have the potential to be used: as sensors for detection, diagnosis, and prognosis, as “blockers/inhibitors” for therapeutics development, and as vectors for the targeted delivery of imaging and therapeutic agents.
vi DEDICATION
This work is fully dedicated to my aunt Carolina and my grandmother Juanita. Thank you for
being my endless flame of inspiration and determination.
“I am no master, I know nothing
I am no master, I know nothing
But I am a servant and I know something
I am no master, I know nothing.”
- Excerpt lyrics from “Black as Night” by Nahko and Medicine for the People
CELL-SURFACE GLYCAN-LECTIN INTERACTIONS
FOR BIOMEDICAL APPLICATIONS
LIST OF TABLES ...... xii
LIST OF FIGURES ...... xiii
LIST OF SCHEMES ...... xvi
LIST OF ABBREVIATIONS ...... xvii
CHAPTER 1 INTRODUCTION ...... 1
1.1. Overview - carbohydrate recognition in biological systems ...... 1
1.2. Principles of glycan recognition...... 5
1.2.1. The “cluster glycoside effect” in carbohydrate recognition ...... 7
1.2.2. Cooperativity vs. polyvalency ...... 11
1.2.3. Enthalpy of a polyvalent interaction ...... 13
1.2.4. Entropy of a polyvalent interaction ...... 13
1.3. Lectins ...... 16
1.3.1. Types of lectins ...... 19
1.4. Lectin-carbohydrate interactions: towards therapeutic and diagnostic
applications ...... 25
1.6. Research goals ...... 27
CHAPTER 2 THERMODYNAMIC ASSESSMENT OF MUC1-TYPE GLYCOPEPTIDES
AND ITS EFFECT ON GALECTIN-3 BINDING ...... 30
2.1. Overview ...... 30
2.2. Galectin-3 ...... 30
2.3. The Thomsen-Friedenreich antigen (TF) and its role in cancer ...... 31 viii 2.4. MUC1 glycopeptides ...... 36
2.5. Peptide modification by glycosylation ...... 37
2.6. Thermodynamic assessment study ...... 38
2.6.1. Assessment of binding interaction of glycosides with galectin-3 ...... 38
2.6.2. Assessment of binding interaction of glycopeptides with galectin-3 ...... 40
2.7. Discussion and conclusions ...... 44
2.8. Materials and methods ...... 46
2.8.1. Chemicals and instrumentation ...... 46
2.8.2. Bacterial strains and reagents ...... 46
2.8.3. Galectin-3/Gal3C expression and purification ...... 46
2.8.4. Isothermal titration calorimetry measurements ...... 48
CHAPTER 3 STRUCTURAL MODIFICATION OF NATIVE ODORRANALECTIN (OL)
PEPTIDES AND ITS EFFECT ON STABILITY, L-FUCOSE BINDING AND HUMAN CELL
TOXICITY ...... 49
3.1. Overview ...... 49
3.2. L-fucose and its role in cancer ...... 52
3.3. Odorranalectin (OL) for potential tumor-targeted therapeutics ...... 55
3.4. Solid-phase synthesis ...... 58
3.4.1. Synthesis of native odorranalectin (OL) ...... 60
3.4.2. Synthesis of the linear analog (OL linear) ...... 61
3.4.3. Synthesis of amide analogs (OLA3 and OLA4) ...... 62
3.5. Conformational study ...... 66
3.5.1. Circular dichroism (CD) spectroscopy ...... 66
3.5.2. Molecular dynamics (MD) simulations ...... 68
3.6. Thermodynamic assessment study ...... 69
ix 3.6.1. Assessment of binding interaction of native OL and its amide analogs with
fucosylated-glycoproteins ...... 69
3.7. In vitro cell study ...... 73
3.7.1. Assessment of binding interaction of native OL and its amide analogs by
in vitro lectin-binding cell-based assay ...... 73
3.7.2. Assessment of binding interaction of native OL by in vitro competitive
inhibition cell-based assay ...... 81
3.8. Cytotoxicity study ...... 83
3.8.1. Toxicity towards human normal and cancer cell lines ...... 83
3.9. Discussion and conclusions ...... 84
3.10. Materials and methods ...... 87
3.10.1. Chemicals and instrumentation ...... 87
3.10.2. Human cell lines and reagents ...... 88
3.10.3. General procedure for peptide synthesis and purification ...... 88
3.10.4. Circular dichroism (CD) spectroscopy ...... 90
3.10.5. Molecular dynamics (MD) simulations ...... 90
3.10.6. Isothermal titration calorimetry measurements ...... 91
3.10.7. Fluorescently-labeled in vitro lectin cell-based assays ...... 92
3.10.8. Fluorescently-labeled in vitro inhibition competitive cell-based assay ...... 92
3.10.9. Cell viability assay ...... 92
CHAPTER 4 DELIVERY OF ODORRANALECTIN (OL) TO THE BRAIN VIA
INTRANASAL ROUTE ...... 94
4.1. Overview ...... 94
4.2. Direct nose-to-brain drug delivery via intranasal administration ...... 95
4.3. Exploitation of fucose for intranasal drug delivery ...... 99
x 4.4. Solid-phase synthesis ...... 100
4.4.1. Synthesis of native odorranalectin (OL) ...... 100
4.4.2. Synthesis of the randomized scrambled analog (SC-OL) ...... 100
4.5. Thermodynamic assessment study ...... 101
4.5.1. Assessment of binding interaction of native OL and its randomly
scrambled (SC-OL) analog with fucosylated-glycoproteins ...... 101
4.6. In vivo intranasal administration study ...... 102
4.6.1. In vivo intranasal administration, tissue collection and processing of native
OL for detection by LC-MS/MS ...... 102
4.7. Discussion and conclusions ...... 103
4.8. Materials and methods ...... 105
4.8.1. Chemicals and instrumentation ...... 105
4.8.2. Animals and reagents ...... 106
4.8.3. General procedure for peptide synthesis and purification ...... 106
4.8.4. Intranasal administration of native OL to mice ...... 107
4.8.5. Tissue collection and processing for native OL detection ...... 107
4.8.6. Native OL detection by LC-MS/MS mass spectrometry ...... 108
APPENDICES ...... 109
REFERENCES ...... 122
xi LIST OF TABLES
Table 1. Comparison of the two major classes of glycan-binding proteins ...... 7
Table 2. Thermodynamic parameters for binding of ASF to the human galectins...... 35
Table 3. Common expression patterns of cancer glycans on malignant tissues ...... 50
Table 4. Key benefits offered by nasal drug delivery systems...... 97
Table 5. Advantages and limitations of nasal drug delivery ...... 98
xii LIST OF FIGURES
Figure 1. Glycoconjugate biosynthesis ...... 2
Figure 2. The major classes of glycan structures ...... 4
Figure 3. Binding modes engaged by polyvalent ligands ...... 9
Figure 4. Schematic diagram of the binding of a glycan to a GBP (lectin) in water,
resulting in displacement of water ...... 12
Figure 5. Schematic examples of the major types of animal lectins, based on protein
structure ...... 20
Figure 6. Schematic illustration of the three members of the selectin family of cell
adhesion molecules and their ligand specificities ...... 22
Figure 7. Different type of galectins in humans ...... 23
Figure 8. Structure comparison on the Tn, sTn and TF antigens ...... 32
Figure 9. Two poses for the TF antigen bound to galectin-3 in the NMR consistent
trajectory of the manually docked ligand ...... 33
Figure 10. Human galectin-3 carbohydrate binding site interacting with the bound LacNAc
moiety ...... 34
Figure 11. ITC titration profile for galectin-3/galectin-3 CRD with tumor-associated
antigens ...... 39
Figure 12. ITC titration profile of galectin-3 with LacNAc and MUC1-type glycopeptides ...... 41
Figure 13. ITC titration profile of galectin-3 CRD with LacNAc and MUC1-type
glycopeptides ...... 43
Figure 14. Thermodynamic profiles of galectin-3 and galectin-3 CRD with carbohydrates
and MUC1-type glycopeptides ...... 45
Figure 15. SDS-PAGE of A) galectin-3 and B) galectin-3 CRD ...... 48
xiii Figure 16. Structures of carbohydrate determinants having fucose-binding activity ...... 51
Figure 17. A) Example of an N-glycan structure containing some of the main
carbohydrate alterations found in tumors: β(1,6)-branching, sialylation, core
fucosylation, and sialyl-Lewis antigens; B) α-L-fucose and α-D-galactose structure
comparison ...... 53
Figure 18. Key features of OL ...... 57
Figure 19. OL cysteine-to-amino acid substitutions for disulfide bridge replacement amide
bonds ...... 60
Figure 20. Circular dichroism (CD) spectra of native OL and its analogs in 0.5% AcOH
and 100% TFE ...... 67
Figure 21. Backbone overlays of native OL peptide with its amide analogs ...... 69
Figure 22. Isothermal titration calorimetry (ITC) data of native OL and its amide analogs
with fucosylated glycoproteins ...... 71
Figure 23. Structures of OL analogs used in the in vitro cell-based studies ...... 75
Figure 24. Cell-based lectin studies with fluorescently labelled lectins ...... 76
Figure 25. Fluorescence readout for each cell line with their corresponding fluorescently-
labeled lectins (SNA-FITC, UEA1-FITC, and AAL-FITC) ...... 77
Figure 26. Cell-based lectin studies with fluorescently labelled peptides ...... 80
Figure 27. Cell-based lectin studies with fluorescently labelled peptides. Fluorescence
readout for each cell line with their corresponding fluorescently-labeled peptides...... 81
Figure 28. Competitive binding assay of OL with cancer and normal cell lines...... 82
Figure 29. Cell viability assay shown as percentage (%) viability with BJ cell line (10,000
cells/well) and OL, OLA3, and OLA4 at different concentrations ...... 83
Figure 30. Pathways for brain delivery after intranasal administration ...... 95
Figure 31. A) Anatomy of the nose and brain; B) Potential transport routes for substances
into the brain ...... 96
Figure 32. Pathways across the blood-brain barrier (BBB) ...... 98
xiv Figure 33. Isothermal titration calorimetry (ITC) data for randomly scrmabled OL peptide
analog (SC-OL) (3 mM) with ASF (250 uM) ...... 101
Figure 34. Detection of OL in mouse nose, brain and olfactory nerve based on average
peak ratio given by the m/z of parent and fragment ion and the IS in LC-MS/MS ...... 102
Figure 35. RP-HPLC chromatogram trace (above) and MALDI-TOF spectrum (below) of
native OL ...... 110
Figure 36. RP-HPLC chromatogram trace (above) and MALDI-TOF spectrum (below) of
OLA3 ...... 111
Figure 37. RP-HPLC chromatogram trace (above) and MALDI-TOF spectrum (below) of
OLA4 ...... 112
Figure 38. RP-HPLC chromatogram trace (above) and MADI-TOF spectrum (below) of
OL linear ...... 113
Figure 39. RP-HPLC chromatogram trace (above) and MADI-TOF spectrum (below) of
OL-FAM ...... 114
Figure 40. RP-HPLC chromatogram trace (above) and MADI-TOF spectrum (below) of
OLA3-FAM ...... 115
Figure 41. RP-HPLC chromatogram trace (above) and MADI-TOF spectrum (below) of
OLA4-FAM ...... 116
Figure 42. RP-HPLC chromatogram trace (above) and MALDI-TOF spectrum (below) of
SC-OL ...... 117
Figure 43A-B. OL peptide detection in nose tissue samples after 30 min intranasal
administration ...... 118
Figure 44A-B. OL peptide detection in brain tissue samples after 30 min intranasal
administration ...... 120
xv LIST OF SCHEMES
Scheme 1. The TF-glycosylated MUC1-peptides used in this study...... 38
Scheme 2. Possible disulfide bridge replacements used in peptide chemistry...... 59
Scheme 3. Fmoc-solid phase peptide synthesis of native OL and its linear analog...... 61
Scheme 4. Aspartimide (Asi) side-product formation seen in Fmoc-Asp-OAllyl after
standard Fmoc deprotection conditions...... 63
Scheme 5. Fmoc-solid phase peptide synthesis of odorranalectin amide analog 3 (OLA3) ...... 64
Scheme 6. Fmoc-solid phase peptide synthesis of odorranalectin amide analogue 4
(OLA4) ...... 65
xvi LIST OF ABBREVIATIONS
AAL Aleuria aurantia lectin
ACN Acetonitrile
AcOH Acetic acid
Alloc, Aloc Allyloxycarbonyl
AMT Absorptive-mediated transcytosis
ASF Asialofetuin
Asi Aspartimide
ATP Adenosine triphosphate
BBB Blood-brain barrier
BCSFB Blood-cerebrospinal fluid barrier
BME β-mercaptoethanol
Boc tert-Butoxycarbonyl
CAA Cancer-associated antigen
CD Circular dichroism
CMT Carrier-mediated transport
CNS Central nervous system
CPP Cell-penetrating peptide
CRC Colorectal cancer
CRD Carbohydrate recognition domain
CSF Cerebrospinal fluid
CTLD C-type lectin domain
Da Dalton
DBU 1,8-Diazabicyclo[5.4.0]undec-7-ene
xvii DCM Dichloromethane
DIC Diisopropylcarbodiimide
DIEA Diisopropylethyl amine
DKP Diketopiperazine
Dmab 4-(N-[1-(4,4-dimethyl-2,6-dioxocyclohexylidene)-3-
methylbutyl]amino)benzyl
DMF N,N’-Dimethylformamide
DMSO Dimethyl sulfoxide
EDTA Ethylenediaminetetraacetic acid
EGF Epidermal growth factor
ELISA Enzyme linked immunosorbent assay
EMEM Eagle’s minimum essential medium
Eq Equivalent
ER Endoplasmic reticulum
EtOAc Ethyl acetate
EtOH Ethanol
FAM Fluorescein
FBS Fetal bovine serum
FITC Fluorescein isothiocyanate
Fmoc Fluorenylmethyloxycarbonyl
Fuc Fucose
GAG Glycosaminoglycan
Gal Galactose
Gal3C Galectin-3 carbohydrate recognition domain (CRD)
GalNAc N-acetylgalactosamine
GBPs Glycan-binding proteins
GI Gastrointestinal
GlcNAc N-acetylgluctosamine
xviii
Glu Glucose
HBTU 2-(1H-Benzotriezole-1-yl)-1,1,3,3-tetramethyluronium
hexafluorophosphate
HCC Hepatocellular carcinoma
HOAt N-Hydroxy-7-azabenzotriazole
HOBt N-Hydroxybenzotriazole
Hpt Haptoglobin
HTS High-throughput screening
IC50 Inhibitory concentration 50
IgSF Immunoglobulin superfamily
ITC Isothermal titration calorimetry
IPA Isopropanol
IPTG Isopropyl β-D-1-thiogalactopyranoside kDa Kilo dalton
Lac Lactose
LacNAc N-Acetyllactosamine (Galβ1-4GlcNAc)
LB Luria Bertani
LC Liquid chromatography
LC-MS/MS Liquid chromatography tandem mass spectrometry
M6P Mannose-6-phosphate
MALDI-TOF MS Matrix-assisted laser desorption/ionization time-of-flight mass
spectroscopy
Man Mannose
MD Molecular dynamics
MeOH Methanol
Mtt 4-Methyltrityl chloride
MR Mannose receptor
MS Mass spectrometry
xix
MW Molecular weight
MWCO Molecular weight cut-off
NMM N-Methylmorpholine
NMP N-Methylpyrrolidone
NMR Nuclear magnetic resonance
NP Nanoparticle
OL Odorranalectin
Pbf (pentamethyl-2,3-dihydrobenzofuran-5-sulfonyl)
PBS Phosphate buffered saline
PD Pharmacodynamics
PEG Polyethylene glycol
PK Pharmacokinetics
PMRI Partially modified retro-inverso
PyBOP Benzotriazol-1-yl-oxytripyrrolidinophospphonium hexafluorophosphate
RMSD Root-mean-square deviation
RMT Receptor-mediated transcytosis
RP-HPLC Reverse-phase high performance liquid chromatography
SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis
SPPS Solid-phase peptide synthesis
SPR Surface plasmon resonance
TACA Tumor-associated carbohydrate antigen
TAT Transcription-transactivating protein tBu tert-Butyl
TF Thomson-Friedenreich antigen
TFA Trifluoroacetic acid
TFE Trifluoroethanol
TM Transmembrane region
Trt Trityl
xx
UEA-I Ulex europaeus I lectin
xxi
CHAPTER 1
INTRODUCTION
1.1. Overview - carbohydrate recognition in biological systems
Carbohydrate recognition is considered one of the most sophisticated recognition processes in biological systems due to the exceptional capacity of oligosaccharides to store the biological information.1-8 It is a well-known fact that most cell surfaces are covered with carbohydrates as well as those on some circulating glycoproteins.9,10 Traditionally considered as bioenergy suppliers, carbohydrates have been found to have a wide variety of biological and physiological functions involving cell-cell interactions. Therefore, it is not surprising that carbohydrates are biomarkers for cell types, disease states, protein functions, and developmental states.11-17 Glycobiology18 has become a popular topic in recent years when frontiers of biological sciences are discussed. Indeed, there are a number of important biological phenomena which depend on carbohydrate-protein interactions.10 Although carbohydrates are ubiquitous in both prokaryotic and eukaryotic cells, an appreciation of their varied functions is only beginning to emerge.1 Carbohydrates exist in diverse forms. Some are attached to protein cores, as in glycoproteins and proteoglycans; others appear as lipids, as in microbial lipopolysaccharides and glycosyl phosphatidylinositol linkages; still others are found as polysaccharides, as in glycosaminoglycans (GAGs), and bacterial capsular polysaccharides.19
Moreover, unlike the proteins and nucleic acids, carbohydrates, due to the presence of multiple functional groups on each monomeric unit, are capable of forming many different combinatorial structures, including branched ones, from relatively small numbers of sugar units.
Each structure potentially carries a specific biological message, thus widening the spectrum of reactivity that is possible from a limited number of monomers.10 Additional structural complexity is achieved by carbohydrate branching, where multiple glycosidic linkages are made to a glycan
1 moiety. Each glycan moiety in a complex carbohydrate can possess up to five hydroxyl groups, and glycosidic linkages to each of them can be in one of two anomeric configurations.19 For example, the monosaccharide D-glucose can be substituted at any of the hydroxyl groups located on carbons C2, C3, C4, C6 and at either of the two anomeric positions. By contrast, nucleotides
(e.g. deoxyadenosine monophosphate) and amino acids (e.g. serine) form linear polymers with just one mode of connection in each case.20 Indeed, it has been calculated that six carbohydrate monomers can yield >1012 oligomeric structures (compared to 4,090 for nucleotides and 6 x 107 peptides).21 As a result, even relatively short oligosaccharides have a far greater capacity for structural diversity than either peptides or oligonucleotides with a similar molecular weight.22,23
Although this structural diversity renders carbohydrates exquisitely suited to the transfer of information, it also underscores the need for methods that can analyze the numerous interactions
(including cell-cell, glycan-protein/lectin, and glycan-glycan) with many different types of glycan structures.19
Figure 1. Different types of processes that involve carbohydrate recognition in biological systems.
Natural carbohydrate recognition is mediated by various classes of proteins.2,25 Leaving aside the enzymes whose function is to both bind and transform carbohydrate substrates, important categories are: a) antibodies, of which over 70% (when induced by whole cells) are normally directed toward oligosaccharide epitopes,26 b) the lectins, which are used by animals,
2 plants, bacteria and viruses for the recognition of cell-surface oligosaccharides, and c) the bacterial periplasmic proteins, part of the glycan-binding proteins (GBPs)2,25 which are involved in carbohydrate transport and chemotaxis in Gram-negative organisms27,28,24 (Figure 1).
The major classes of glycan structures are shown in Figure 2. N-linked glycans are attached to an asparagine residue of a protein carrier with the sequence Asn-Xaa-Ser/Thr (Xaa can be any amino acid except Pro),29and consists of three main classes: oligomannose, complex- and hybrid-type sugars.31 O-glycans are covalently α-linked via an N-acetylgalactosamine
(GalNAc) moiety to the OH of Ser and/or Thr by an O-glycosidic bond. There are also several types of O-glycans, such as sialylated core 1 mucin-type O-linked sugar, β-linked O-GlcNAc (N- acetylglucosamine) and α-linked O-Fuc, β-linked O-xylose, α-linked O-mannose, O-GlcNAc, α/β- linked O-galactose, and α/β-linked O-glucose glycans. Proteoglycans have GalNAc as the first sugar.31 Glycan structures can vary from highly branched and complex glycans (N- and O-linked glycans and glycolipids) to linear glycans (photeoglycans). Due to the large number of possible structures, the information content of glycans is enormous. N-glycosylation is initiated in the endoplasmic reticulum (ER) and renders highly branched structures which play key roles in cell- to-cell contact, cell-extracellular matrix interactions and thus adhesion,29 while O-linked glycosylation is normally initiated in the Golgi apparatus, and subsequently a stepwise enzymatic elongation by specific transferases yields several core structures, which are further elongated or modified by sialylation, sulfatation, acetylation, fucosylation, and polylactosamine-extension.31-33
3
Figure 2. The major classes of glycan structures.30
In addition to direct effects on biological activity, sugar addition appears to alter many physicochemical and pharmacological properties of the peptide backbone. Consequently, both O- and N-linked glycosylation have been often used to improve various less than optimal features of peptide drug leads. Compounds that can specifically recognize a particular carbohydrate may have very important biomedical applications.27,34-36 They can be used as sensors for detection, diagnosis, and prognosis, as “blockers/inhibitors” for therapeutics development if the target carbohydrate is involved in pathogenesis, and as vectors for the targeted delivery of imaging and therapeutic agents. Critical to all these potential applications are two issues: (1) the identification of carbohydrate biomarkers, and (2) the design and synthesis of “binders” that can specifically recognize the target biomarker with high affinity and specificity.17
4
1.2. Principles of glycan recognition
Molecular recognition is key feature used by nature. Biomolecules such as peptides, nucleic acids and carbohydrates exhibit intrinsically encoded recognition properties in living systems.37 Glycosylation is the most abundant post-translational modification, with more than
50% of the proteins occurring in humans being glycoproteins; these play a significant role in biological processes, such as immune-differentiation, cell adhesion, cell differentiation, and regulation of cell growth.1,38-40 Furthermore, the biological selectivity role of glycoproteins is most often played by the carbohydrate residue.41,42 Binding of glycans to proteins represents the major way in which the information contained in glycan structure is recognized, deciphers, and put into biological action.39 The distinct functions served by these proteins are reflected in their intrinsic affinities for monosaccharides, as some have high affinity towards their ligands than others.27
In nature, carbohydrate-binding proteins and lectins are typically aggregated into higher- order oligomeric structures, existing as monodisperse entities or as aggregates of very high valency, similar to viral particles. If nature has circumvented the tight binding limitation through polyvalency, it seems reasonable that polyvalent ligands should bind with high affinity as well.43
Many biological interactions and functions are mediated by glycans, leading to the emerging importance of carbohydrate and glycoconjugate chemistry in the design of novel drug therapeutics. However the case may be, it is clear that glycoconjugates have many and varied functions. The same structure can have multiple roles due to temporal and spatial differences in the oligosaccharide expression, as well as inter- and intra-species variations in glycosylation.1 It is reasonably clear that biological roles of oligosaccharides can range from those that are trivial to those that are critical for the development, growth, function, and survival of an organism. Review of the matter suggests that terminal sequences as well as unusual structures and modifications of oligosaccharides are more likely to mediate specific biological roles.
Excluding glycan-specific antibodies44 it is possible to classify GBPs broadly into two major groups: groups I and II (Table 1).25,45,46 The carbohydrate-binding sites of group I proteins are located in deep clefts and binding leaves little or no part of the ligand exposed to the bulk solvent. Carbohydrate binding by this class of proteins is high-affinity, typically with sub-
5 micromolar dissociation constants. This group includes the bacterial periplasmic binding proteins, certain enzymes that act on sugar substrates, and glycosaminoglycan-binding proteins.27 In contrast, the binding sites of group II proteins, which include the lectins, tend to be on the surface of the protein and are rather shallow clefts. Binding affinities are lower than for group I proteins
(millimolar range).27 Most lectins are members of families with defined “carbohydrate-recognition domain” (CRDs) that apparently evolved from shared ancestral genes, often retaining specific features of amino acid sequences or three-dimensional structure. Lectins tend to recognize specific terminal aspects of glycan chains by fitting them into shallow, but relatively well-defined binding pockets. In contrast, protein interactions with sulfated glycosaminoglycans seem to involve surface clusters of positively charged amino acids that line up against internal regions of extended anionic glycosaminoglycan chains.25 Glycosaminoglycans are one of the most important cancer saccharides. They are functional linear heteropolysaccharides which participate in and regulate a number of cellular events and physiological/pathological processes.47,48
Despite the differences between group I and II proteins, many features of carbohydrate recognition are shared, with differences reflected primarily in the number of contacts formed and the degree of shielding from aqueous solution. In group I proteins, virtually all of the hydrogen bonding potential of the sugar is used, including that of the ring oxygen, whereas the lectins form hydrogen bonds with only a subset of the OHs of the sugar. Moreover, in lectins, a significant portion of the sugar ring is exposed to water, which is important in allowing recognition of different substituents at particular ring positions. In contrast, group II proteins undergo a large conformational change that buries the entire sugar from bulk water. In this case, it would be energetically costly to have unsatisfied hydrogen bonds. The larger number of hydrogen bonds formed in expelling large numbers of water molecules when the protein closes around the ligand, is believed to provide tight affinity displayed by this class of proteins when compared to lectins.46
This is mainly due to an enhancement of affinity through hydrophobic interactions, even at the expense of hydrogen bonds.49
6
Table 1. Comparison of the two major classes of glycan-binding proteins.25
Group II Group I Characteristics (Glycosaminoglycan- (Lectins) binding proteins) Shared evolutionary origins Yes (within each group) No Shared structural features Yes (within each group) No Defining a-a residues Patch of basic amino Often typical for each group involved in binding acid residues Sulfated Type of glycans recognized N- and O-glycans, glycolipids glycosaminoglycans Typically in sequences internal to an extends Location of cognate residues Typically in sequences at outer ends sulfated within glycans of glycan chains glycosaminoglycan chain Often recognize a range Specificity for glycans Stereospecificity high for specific of related sulfated recognized glycan structures glycosaminoglycan structures Often low; high avidity generated by Single-site binding affinity Often moderate to high polyvalency
Polyvalency common (either within Valency of binding sites Often monovalent native structure or clustering) Heparin sulfate-, C-type, galectins, P-type, I-type, L- chondroitin sulfate-, Subgroups type, R-type lectins, etc. dermatan sulfate- binding proteins Classification itself is Types of glycans recognized Can be similar (e.g. galectins) or based on type of within each group variable (e.g. C-type lectins) glycosaminoglycan chain recognized
1.2.1. The “cluster glycoside effect” in carbohydrate recognition
The function of many carbohydrates is contingent on their polyvalent presentation. The binding of proteins to monovalent carbohydrate determinants is often weak, as is the case for lectins, yet the strength and specificity required for recognition in physiological settings found in
Nature is high.24 What are the physiological advantages conferred by polyvalent binding? Relative to monovalent binding, polyvalent interactions exhibit greater reversibility in the presence of competing ligands.50 Thus, low affinity, polyvalent interactions are less likely to entrap cells in unproductive binding events.24 In addition, binding event mediated by multiple weak interactions is expected to be more resistant to shear stress, such as that encountered when cells interact in the bloodstream.51 Biologically relevant recognition requires specific glycoconjugates that
7
“present” multiple copies of such oligosaccharides in a specialized fashion, by proper spacing on the linear polypeptide chain, and in the proper three-dimensional context.1 If the molecules in question are present in high copy number on the cell surface (e.g. glycolipids), the summing of a large number of relatively low-affinity interactions could result in a substantially higher avidity, sufficient for biological significance. Such a “Velcro” effect may be well sufficient to mediate biologically relevant recognition.1 There are several distinct mechanisms that contribute to the high activities often observed for polyvalent ligands in biological systems.24 An understanding of these is critical for optimizing ligand performance and for understanding how natural systems function. Different ways to consider polyvalent effects are shown in Figure 3.24 (1) the “chelate effect”, (2) occupation of adjacent subsites, and (3) ligand-induced protein clustering.24,52 When the “chelate effect” operates, multiple interactions occur after formation of the first contact; these are facilitated because of high effective concentration of the binding groups.53 The statistical of proximity effect causes an increase in the effective concentration of the ligand, and occurs when multiple ligands are clustered around the binding site of a receptor.52 This mode of binding can enhance the affinity if the orientation and display of binding groups are favorably disposed.
Because multipoint binding typically involves ligand organization, it exacts a conformational entropy penalty that may offset the advantages of chelation.52 The “chelate effect” occurs because binding of a polyvalent ligand to multiple binding sites on a multi-point receptor is more favorable than binding of multiple monovalent ligands to the same receptor. Bivalent (or higher) interactions occur when multiple binding sites on a multi-point receptor are simultaneously occupied either by the same carbohydrate-functionalized platform of multiple glycosystems.52,54
All of these models can proceed to higher aggregates. Many factors, including thermodynamic and kinetic effects, aggregation, clustering, and effective concentration, contribute to polyvalent effects.52 Alternatively, polyvalent displays may be effective ligands because they occupy subsites as well as the primary binding site on the target protein.24 Lastly, the activities of many small and large polyvalent carbohydrate derivatives are due to their abilities to cluster their receptors.55,56 Thus, polyvalent ligands can exhibit a wide range of different activities, depending on their binding modes.24
8
Figure 3. Binding modes engaged by polyvalent ligands. (A) Polyvalent ligands can bind oligomeric receptors by occupying multiple binding sites (chelate effect), (B) occupying primary and secondary binding sites on a receptor, and (C) causing receptor clustering in the membrane.24
The “cluster glycoside effect”, defined as “the enhancement in the activity of a polyvalent ligand beyond what would be expected due to the increase in sugar local concentration (statistical effect) alone.57 In a first approximation, a trend of increased enhancement with increasing valency can be drawn.58 In principle, at least two models of association can be described: an intramolecular, or chelate, binding and an intermolecular aggregative process. In the former, a polyvalent ligand spans a number of binding sites on a single protein, while in the latter the spanned binding sites belong to different receptor molecules, resulting in aggregates that may or may not precipitate.58 A strong “glycoside cluster effect” requires two partners: a receptor (e.g. lectin) with clustered sugar binding sites and a polyvalent ligand that can present sugars with proper orientation and spacing.10
The key thermodynamic principle in polyvalency is that, ideally, the enthalpy of binding of a polyvalent system is more favorable than that of the monovalent species, with little or no corresponding increase in the unfavorable translational and rotational entropy of binding.59
Polyvalent ligands often possess increased functional affinity (the apparent affinity for the interaction) for their targets compared with that of monovalent ligands.60 The enthalpy of
9 interaction of a polyvalent ligand with a polyvalent receptor is, in principle, additive (the enthalpy of interaction of three ligands with a receptor is three times the enthalpy of interaction of a single ligand), while the entropy of interaction is not (since the three ligands are connected, association of one ligand with one receptor increases the local concentration of the other ligands and receptors, and decreases the unfavorable entropic penalty “paid” to bring ligands and receptors together).59 Conformational flexibility can be a major factor limiting the affinity and specificity of interactions. Molecules than can easily undergo induced fit will be able to interact with a variety of targets, but will pay the price of decreased affinity due to a conformational energy penalty. On the other hand, molecules with well-defined solution ground states that naturally complement the desired target will bind to fewer targets, but will do so with higher affinities.61
Multiple protein-carbohydrate interactions could cooperate in each recognition event to give the necessary functional affinity. This means that multiple receptors must be arranged in such a way as to bind efficiently to multiple saccharide ligands.62 The requirement for the spatial arrangement of the receptors and the binding sites on the ligand to be compatible means that specificity in polyvalent binding could be achieved, not only via complementarity between individual receptor-ligand pairs, but also by controlling the spatial arrangement between individual recognition elements of a polyvalent ligand, or by changing the number of individual interactions.62,63 The lectin concavalin A is a good example where spatial arrangement for molecular recognition between elements is seen.55,64
An example of the use of polyvalency on the binding effect is the trivalent vancomycin·D-
50,65 Ala-D-Ala system that converts an interaction that is moderately strong for the monovalent species into one that is very strong, illustrating the difference in mechanism (manifested in kinetics) between tight-binding oligovalent systems and tight-binding monovalent ones: the trivalent vancomycin·D-Ala-D-Ala complex dissociates rapidly in the presence of competing monovalent ligands (equilibration of 3 µM of the trivalent complex vancomycin·D-Ala-D-Ala with 86
4 65 mM (Kd ~1.7x10 M) of diacetyl-L-Lys- D-Ala-D-Ala was complete in <45 min), while monovalent
-15 complexes of comparable affinity, like biotin-avidin (Kd ~10 M)dissociated slowly (half-life for dissociation ~ 200 days). This kinetic observation illustrates that the mechanism for dissociation
10
(and association) of polyvalent species is qualitatively different than that for tight-binding monovalent species such as biotin-avidin.50,59
1.2.2. Cooperativity vs. polyvalency
The most striking features of lectin-monosaccharide interactions are that they are relatively weak, with dissociation constants in the millimolar range for monosaccharides,10,66 and they may show broad specificity, when compared to the strict nature of enzyme-substrate associations.58 The reason for this weakness lies in the solvent-exposed nature of the lectin binding-sites, which are shallow pockets making few direct contacts with the ligands.22
Nevertheless, lectins exhibit both high affinity and exquisite specificity for oligosaccharide structures of glycoproteins and glycolipids on the cell surface. Multiple protein-carbohydrate interactions must, therefore, be involved in the recognition event, giving the required high affinity and specificity.10 Thus, polyvalent associations occur throughout biology, showing a number of characteristics that monovalent interactions do not exhibit.67,68 In most cases, biological systems seem to use polyvalent interactions rather than a very strong single one. Polyvalency is a design principle in which the operation of multiple molecular recognition events of the same kind occur simultaneously between two entities,67,69 converting a low affinity binding process (~ mM) into a high affinity binding process (~ nM).59 Therefore, polyvalency is employed in Nature not only to achieve the necessary high affinity, but also to ensure the correct functioning of the cells through high specificity.58
Polyvalency and cooperativity are two different phenomena. Cooperativity describes how the binding of one ligand can influence a receptor’s affinity toward further binding interactions.70 It is a phenomenon which occurs when the binding of one ligand to a receptor affects the binding
(that is, the dissociation constant) of additional ligands to the same receptor.59 A cooperative interaction occurs when the binding of one monovalent ligand to one site of a polyvalent protein results in a change in the conformation of the protein (or stabilizes the alternative conformation) that extends to other binding site; this conformational change affects the binding of subsequent ligands to the protein.59 Another common feature of lectin-carbohydrate interactions is the strong
11 linear enthalpy-entropy compensatory behavior.58,71 This offset has been interpreted both in terms of changes in the degrees of freedom of the ligand upon binding,72 and in terms of solvent reorganization (Figure 4).73
Figure 4. Schematic diagram of the binding of a glycan to a GBP (lectin) in water, resulting in displacement of water.25
Assessing cooperativity in polyvalent systems would require consideration of either (1) effective concentrations of interacting groups within the polyvalent ligand, or (2) the additivity of free energies.70 Any thermodynamic parameter (Jo) characterizing the binding of a polyvalent
o ligand (ΔJ obs) to a polyvalent receptor is related to that for the corresponding monovalent ligand
o (ΔJ mono), where n is the valency of the ligand by the expression in Eq. 1. In this context, the
o interaction term (ΔJ int) describes the energetic consequences of physically tethering monovalent ligands.74
The average free energy of interaction between a ligand moiety and receptor moiety in a
poly polyvalent interaction (ΔGN ) can be greater than, equal to, or less than the free energy in the
mono poly poly analogous monovalent interaction (ΔG ). ΔGN is made up of enthalpic (ΔHN ) and entropic
poly 67 (ΔSN ) components, expressed in Eq. 2. The enhancement factor (β), expressed in Eq. 4, has
poly mono been defined as the ratio of the two association constants KN and K , as well as the “ratio of avidity to the component affinity of the monovalent equivalent of the interaction.”67 Molecules that have high values of β are useful because they have high avidity-to-affinity (of the equivalent
12 monovalent) ratio, regardless of whether the interactions that generate them are cooperative or not.67
1.2.3. Enthalpy of a polyvalent interaction
poly As a first approximation, the value ΔHN , expressed in Eq. 2, is the sum of the enthalpies of N monovalent interactions (NΔHmono). This value may be either larger or smaller by other interactions around the active site.67 In some cases, the binding of one ligand to a receptor with a given enthalpy may cause the next ligand to bind to its receptor with greater enthalpy; that
poly mono is, the value of ΔHN is in this case more negative (more favorable) than the value of ΔH . If the binding of one ligand to its receptor interferes with the next binding event, the enthalpy of the polyvalent interaction is less favorable than that expected for N equivalent monovalent interactions.67 Such binding is enthalpically diminished, and can occur when formation of multiple ligand-receptor interactions between two polyvalent entities requires energetically unfavorable molecular conformations.67 As a rule of thumb, the more conformationally rigid the polyvalent entity is, the more likely it is that even small spatial mismatches between the ligand and its receptor will result in enthalpically diminished binding.67
1.2.4. Entropy of a polyvalent interaction
As we have seen from Eq. 2, both entropic and enthalpic terms contribute to interaction free energies, and from an entropic perspective, entropic energies are typically considered largely as a balance between a favorable translational/rotational interaction entropy and an unfavorable conformational interaction entropy.74
poly poly In addition to ΔHN , Eq. 2 also expresses the total entropy of a polyvalent interaction (ΔSN ),
poly which is expressed in Eq. 5 in terms of contributions from changes in translational (ΔStrans,N ),
poly poly rotational (ΔSrot,N ), and conformational entropies (ΔSconf,N ) of the receptors and ligands on
13 association, and a contribution accounting for changes in the entropy of the surrounding water
poly (ΔSwater,N ).
The translational entropy (ΔStrans) of a molecule arises from its freedom to translate independently through space, and is inversely related to the logarithm of its concentration (ΔStrans) while the rotational entropy (ΔSrot) arises from the freedom of the particle to rotate around all three of its principle axis.67 When two particles associate, translational and rotational degrees of freedom are lost, and the total translational and rotational entropic cost of associating a two particles is approximately the same, provided they are at the same concentration.67 Because translational and rotational entropies scale as the logarithm of the molecular weight, this effect results in increase of entropy with decreasing concentration.67,74
The conformational entropy (ΔSconf) is almost always less than zero (unfavorable) on complexation; that is, the number of conformations available to a polyvalent ligand before complexation is greater than that following complexation.67 If this conformational cost is less than the total translational and rotational cost (ΔSconf < ΔStrans + ΔSrot), then the total entropic cost of a polyvalent association is still less than the monovalent case, and binding is still entropically enhanced.67 In the case where this conformational cost equals the total entropic translational and rotational cost (ΔSconf = ΔStrans + ΔSrot), the binding is entropically neutral and the total energetic cost of complexing the second ligand on the dimeric species is the same as the entropic cost of complexing a second dimeric species.67 When the conformational entropic cost of complexing the second ligand of the dimeric species can exceed the translational and rotational entropic cost
(ΔSconf > ΔStrans + ΔSrot), then the second ligand of the dimeric species will never outdo the binding of a second dimeric species, and the binding is entropically diminished.67 And finally, the
poly change in total entropy of the surrounding molecules of water (ΔSwater,N )is often largely due to the entropy of hydrophobic interactions.67 This is largely due to the release of organized water from exposed surfaces of the biological molecules and the resulting increase in entropy.67
In addition, cooperativity in polyvalent interactions can be assessed by considering the
69 inter-and intramolecular processes (ΔG°inter and ΔG°intra) separately and independently, via two
14 microscopic binding energies.75 The term “avidity binding energy”75 is postulated and considered to consist of three major elements: (a) intrinsic free binding energy of initial bimolecular reaction of anchoring to a receptor by single branch of a ligand, (b) intrinsic free binding energy for intramolecular binding of ligand branches to the remaining binding sites on the receptor surface, and (c) a combinatorial factor reflecting the probability of association and dissociation of individual branches.75 The latter two are major determinants of the free energy increase of a polyvalent association with respect to the corresponding monovalent binding.75 A comparison of experimental and statistical association constants for intramolecular interactions, an indication of the extent of cooperativity can be attained.69 Such an assessment can be made using Eq. 4, which determines the statistical (or noncooperative) ratio of association constants for i monovalent ligands interacting with a polyvalent receptor with n binding sites.70
In positive cooperativity (synergistic), the dissociation constant (Kd,n) for the binding of a ligand to a receptor already bound to n ligands, is smaller than the dissociation constant for the
59,76 binding of a ligand to the receptor bound to n-1 ligands (Kd,n-1). This can also be interpreted in terms of association constant , when the experimental ratio of Ki+1/Ki is larger than the theoretical ratio calculated in Eq. 1.70 Thus, a subsequent binding of another molecule is higher than that for the previous one.70 The binding isotherm for a positively cooperative system is steeper than that for a system with independent sites.77 Positive cooperativity allows a large response to small changes in concentration, producing high sensitivity to small perturbations in ligand or substrate concentration.77 However, tight binding does not require positive cooperativity in the sense that this phrase is traditionally used.67 In this sense, the free energy of binding of each ligand in a polyvalent complex does not have to correlate positively with the number of ligand molecules bound.67 Thus, although polyvalent interactions contributing to it, the monomeric interactions may still be interfering with, or indifferent to, one another.67 Such is the case with negative and noncooperative binding.
In the case of negative cooperativity (interfering), Kd,n is greater than Kd,n-1, therefore the
70,76 subsequent binding is lower. In terms of association constant, the Ki+1/Ki is smaller than the
15 theoretical ratio calculated in Eq. 1.70 In this case, the binding curve rises toward saturation more slowly than for a system of independent sites.77 Negative cooperativity manifests itself through a progressive loss of binding affinity within the same class of sites, which is something quite apart from having multiple independent classes of sites with constant affinity for the ligand, and that may also differ in number of binding sites.77 Negative cooperativity tends to keep the activity relatively constant over substantially larger swings in concentration. That is, negative cooperativity can desensitize the system to fluctuations in concentration.77 In a system with no
70 cooperativity (additive), Kd,n is equal to Kd,n-1, meaning the binding is equal and the sites are acting independently.77 Binding of the ligand species occurs at random, with equal a priori probability at any vacant site.77
1.3. Lectins
Lectins (from lectus, the past participle of legere, to select or choose),78 are defined as carbohydrate binding proteins other than enzymes or antibodies,58,79 and are recognized as proteins of non-immune origin that identify, and reversibly bind to, specific carbohydrate motifs.66,80 Lectins form a large group of over more than 200 proteins,4 which are widely found in nature,81 including most living organisms, ranging from viruses and bacteria to plants.36,58 Lectins were first discovered in plants more than 100 years ago, and they have been tremendously useful as tools for chemistry and biology that involve carbohydrate recognition, for example, differentiating cell types by cell surface carbohydrates. Some lectins are also receptors, i.e., they can bind carbohydrate-containing ligands and transport the bound ligands to different destinations inside the cells.10 Originally isolated from plants, lectins in history have been exploited for their ability to agglutinate certain types of cell (dependent on the cell-surface carbohydrates present) and also to induce mitosis.28,82 Animal lectins have been shown to be involved in diverse biological processes80,81 in many species,83 such as clearance of glycoproteins from the circulatory system,84,85 adhesion of infectious agents to host cells,86 recruitment of leukocytes to inflammatory sites,87 cell interactions in the immune system, in malignancy and metastasis.25,58,81,88 Lectins, especially those from plants which can be easily obtained in large
16 quantities, have also been widely used to isolate carbohydrate ligands from cells by affinity chromatography and as tools for investigating the structural and functional aspects of carbohydrates in biological systems. The biological activities of lectins are due to their carbohydrate binding properties,25 although some lectins possess non-carbohydrate binding sites.81 The endogenous glycan-binding proteins translate this carbohydrate-encoded biological information into the biological responses based on their ability to distinguish between closely related glycan structures. Hence, it is important to elucidate the carbohydrate binding properties of a lectin in order to understand its biological functions.
Lectins interact with carbohydrates non-covalently in a manner that is usually reversible and highly specific.66 More specifically, lectins bind to carbohydrates through a network of hydrogen bonds and hydrophobic interactions.27,28,58 Protein-carbohydrate recognition is generally established through networks of hydrogen bonds and complementary contacts between nonpolar surfaces.49 Interestingly, the non-polar residues on the protein are almost always aromatic, suggesting a role for specific CH-π interactions.28,89,90 Van der Waals forces, although rather weak (usually a fraction of 4.2 kJ mol-1 for each pair of atoms), are frequently numerous, contributing significantly to the overall binding.36 The steric disposition of hydroxyl groups in carbohydrates creates hydrophobic patches28,82 on the sugar surface that can interact with hydrophobic regions of the protein.58,90-92 For the lectins, most of the hydrogen bonds involve planar, polyvalent side chain groups (Asn, Asp, Glu, Gln, Arg, His).27,93 Metal ions such as Ca2+ are required for full activity of many lectins (including concavalin A), but only for the C-type lectins
(e.g. mannose-binding protein) have direct metal-carbohydrate interactions been observed.28
Contacts between the ligand and the protein are often mediated by water molecules. Water acts as a molecular “mortar,”94 its small size and its ability to behave as both hydrogen donor and acceptor make it near-ideal for this function. Tightly bound water molecules can, in effect, be considered as structural, i.e. an extension of the protein surface. Thus, water plays a significant role in carbohydrate recognition (Figure 4).25,58
Despite their importance in these specific recognition processes, the carbohydrate binding sites are typically shallow binding pockets, where only binding of the terminal mono- and
17 oligosaccharides can occur,10,95,27,28 and as a result, binding of an individual lectin to a
3 4 monosaccharide is very weak (in biological terms), with Ka values typically in the region 10 – 10
-1 10,94 M (Kd = 0.1 - 10 mM) of low affinity, and sometimes, broad specificity within the same
24,62 monosaccharide. Regardless of the weak affinity between lectins and monosaccharides (Kd in the millimolar range), sugar/protein interactions prove to be highly efficient and specific96 due to the fact that extended binding regions lead to much stronger attachment to oligosaccharides in some cases,64 while others the provision of multiple binding sited and-or the tendency of lectins to aggregate, results in high affinities for polyvalent substrates (“glycoside cluster effect”).10 Lectin calorimetric studies have shown that protein-carbohydrate complexation provides an excellent example of “enthalpy-entropy compensation.”28,97,98 Thermodynamic data94 reveals lectin binding enthalpies that vary from -2.0 to -22.0 kcal mol-1, while free energies range between -2.8 and -8.5 kcalmol-1. The spread of binding free energies is reduced by entropies which decrease in step with the enthalpies. Thus, as plot of -ΔH˚ versus -ΔS˚ reveals points scattered fairly closely about a line of gradient 1.05. At one end of the scale (-ΔH˚ = small), ΔS˚ is just positive (favoring binding). However, for most of the range ΔS˚ is negative and opposes complexation.28 Lectins undergo few, if any, changes in conformation upon binding to sugar.27 In no case have global changes in protein structure been observed; instead, small movements are restricted to the immediate vicinity of the sugar.99,100 Ligand binding reduces the amount of conformational variability of certain residues by selecting from the ensemble in solution the conformation that optimizes the contacts.27 The binding sites of lectins appear to be preformed, with ordered water molecules forming hydrogen bonds with the un-liganded proteins in a pattern that closely mimics the hydrogen bonding by sugar OHs.101 This effect is a consequence of the use of planar hydrogen-bond donors and acceptors, which provide fixed geometry for interaction with ligands, and of interactions among amino acid residues and sometimes divalent cations in the binding site that maintain the conformation of the side chain in the absence of sugar ligands.27
18
1.3.1. Types of lectins
Most lectins belong to three classes: (1) simple, (2) mosaic (or multidomain), and (3) macromolecular assemblies.58 Simple lectins consist of a small number of subunits, each with a carbohydrate-binding site which are not necessarily identical, and of molecular weights usually below 40 kDa. This class comprises practically all known plant lectins102 (for a detailed review on plant lectins see ref 103), and most members of the mammalian galectin family, a group of β- galactoside specific animal lectins.104 Mosaic lectins are composite molecules consisting of several kinds of protein domains, only of which possesses a carbohydrate- binding site.58 This class includes diverse proteins from different sources: viral hemagglutinins,105 and animal lectins of C-,P- and I-types.106 Macromolecular assemblies are common in bacteria, and are of filamentous organelles consisting of helically arranged subunits (pilins) assembled in well-defined order.58,107
More specifically, the animal lectins can be classified into four groups (Figure 5),25 of which the first two are dominant: (1) C-type l (including selectins), (2) S-type (galectins), (3) P- type (including mannose-6-phosphate-binding lectins), and (4) other types, such as I-type
(immunoglobulin-like lectins), and R-type.108-110 The classification is now based on a polypeptide motif present in each group that is conserved among the lectins. A minimum polypeptide structure that is required for binding carbohydrate ligands is called the carbohydrate recognition domain
(CRD).106 A CRD can exist alone in nature or in tandem with other CRDs of with other protein domains such as transmembrane domain, collagen domain, and epidermal growth factor (EGF) domain.10
19
Figure 5. Schematic examples of the major types of animal lectins, based on protein structure. Examples of some of the major families are shown. The emphasis is on the extracellular domain structure and topology. The following are the defined carbohydrate-binding domains (CRDs) shown: (CL) C-type lectin CRD; (GL) S-type lectin CRD; (MP) P-type lectin CRD; (IL) I-type lectin CRD. Other domains are (EG) EGF-like domain; (IG2) immunoglobulin C2-set domain; (TM) transmembrane region; and (C3) complement regulatory repeat. The number of domains underlying the CRD can vary among family members.25
1.3.1.1. C-type lectins
The C-type lectins are a family of extracellular carbohydrate recognition proteins that though originally classified on the basis of binding characteristics (C-type lections are so named because of their requirement of calcium for binding activity), they are now characterized by a
CRD consisting of ca. 135 amino acids, and have been shown to display different monosaccharide specificities.10,81 C-type lectins display many types of binding selectivity. Several of these lectins bind derivatives of Man and GlcNAc (Man-type ligands), and a second set of C- type lectins bind Gal and GalNAc (Gal-type ligands).27,111 These proteins have a C-type lectin fold, which is a fold with highly variable protein sequence that is also present in many proteins that do not bind carbohydrates (C-type lectin domain [CTLD]-containing proteins).25 C-type lectins and proteins with CTLDs are found in all organisms. The large family of C-type lectins includes
20 collectins, selectins, endocytic receptors, and proteoglycans. Some of these proteins are secreted and others are transmembrane proteins.25 They often oligomerize into homodimers, homotrimers, and higher-ordered oligomers, which increases their avidity for polyvalent ligands. Although they share structural homology, C-type lectins usually differ significantly in the types of glycans that they recognize with high affinity. These proteins function as adhesion and signaling receptors in many immune functions such as inflammation and immunity to tumor and virally infected cells.25
There are at least 17 groups of proteins with CTLDs, which are distinguished by their domain architecture. Well over 100 different proteins encoded in the human genome contain the CTLD.25
Fundamental aspects of the sugar-binding mechanism are shared in the Man-type and Gal-type binding sites. In particular, the 3- and 4-OHs of both types of sugars, although differently disposed, are apical coordination ligands for bound Ca2+, and they form a network of hydrogen bonds with amino acid side chains that also serve as equatorial ligands for this same divalent cation.27
1.3.1.1.1. Selectins
Since all cells are covered with a dense coating of sugars, it has long been predicted that oligosaccharides must be critical determinants of cell-cell interactions.1 Perhaps the best documented example is that of the selectin family of receptor proteins that mediate the adhesion of leukocytes to endothelial cells (L-selectin), the recognition of leukocytes by stimulated or wounded endothelium (E-selectin), and the interactions of activated platelets or endothelium with leukocytes (P-selectin).108,112,113 Inflammatory diseases, such as arthritis, psoriasis, asthma, and diabetes, are characterized by leukocytes homing into the affected tissues.30,114 A crucial first step on the normal entry of circulating lymphocytes into peripheral lymph nodes and leukocyte emigration into inflamed tissues is their adhesion to activated endothelial cells lining blood vessel walls.115 In addition to their role in cancer metastasis, the selectins (E-, P- and L-selectin)116 mediate the transient initial interaction that results in rolling of the leukocytes along the endothelial surface.116-119 The selectins bind sialylated and fucosylated epitopes120 such as sLex, often in sulphate form,116 which comprise a terminal component of glycans on most leukocytes,
21 endothelial cells in the lymph node and the endothelium of inflamed tissues108,112 (Figure 6).116
More specifically, E-selectin is inducibly expressed on endothelial cells, P-selectin is stored in
Weibel-Parade granules of α-granules in endothelial cells or platelets, and translocated at the cell surface by stimulation.116 L-selectin is known to be constitutively expressed on leukocytes.116
Figure 6. Schematic illustration of the three members of the selectin family of cell adhesion molecules and their ligand specificities.116
1.3.1.2. S-type lectins (Galectins)
The galectins are a growing family of soluble β-galactoside-specific proteins of which 15 members have been identified in mammals,121,122 and their expression and distribution appear to be developmentally regulated.58,81,123 They are highly conserved family of lectins defined by common consensus sequences and structures.124-127 Twelve members of the family have currently been identified in mammals and designated as galectin-1 through galectin-12.128 The structures of the mammalian galectins can be identified as prototype (including galectin-1, -2, -5, -
7, and -10) which exist as monomers or homodimers consisting of one carbohydrate recognition domain (CRD), chimera type (galectin-3) that contains a nonlectin N-terminal collagen-like repeat segment connected to the C-terminal CRD, and tandem repeat type (including galectin-4, -6, -8, and -9) composed of two CRD domains in a single polypeptide chain129-132 (Figure 7).25 Many tumors, such as colon, thyroid and breast carcinomas, express both galectins-1 and -3, and it has been suggested that galectins-3 is a metastasis marker.133 Among the degenerative processes that they can mediate, galectins may favor metastasis by binding glycoconjugates of the extracellular matrix and subsequent intravasation of the tumor cell into the blood vessels.58
22
Galectin-1 is involved in inflammation, development, mRNA splicing, differentiation, cell adhesion, and apoptosis of activated T cells.124,126,134 Galectin-3 has also been shown to exhibit roles in regulating inflammation, cell growth, and cell adhesion.124 However, unlike galectin-1, galectin-3 possesses anti-apoptotic effects in a variety of cells, and its expression has been shown to correlate with metastatic potentials of certain cancers.135 The preferential binding of galectins to
N-acetyllactosamine (Galβ1→4GlcNAc, LacNAc) suggests that the functions of these lectins are mediated through their binding to proteins containing LacNAc residues or related structures. A particular target for galectin-3 has been the Thomson-Friedenreich (TF) carcinoma antigen
(Galβ1→3GalNAcα1,R).136-139 It has been suggested that galectin-3 utilizes two subsets of ligands, i.e. cellular and secreted, for different cellular and extracellular functions.127
Figure 7. Different type of galectins in humans. A) Human galectins have been classified into three groups according to their structure: prototypical, chimeric, and tandem repeat. The carbohydrate-recognition domain (CRD) of most galectins is approx. 130 amino acids, and this is indicated by the oval domain. B) Examples of the sequence alignments between several human galectins. The amino acid numbering is shown for galectin-1, which has 135 amino acids in total, but the other galectins are aligned without showing their numbers. Those residues that are highly conserved between galectins and those that are known to make contacts with carbohydrate ligands are indicated by asterisks: (red) conserved hydrophilic residues, (blue) conserved hydrophobic residues. (N-term): amino-terminal. (C-term): carboxy-terminal.25
23
1.3.1.3. P-type lectins
The P-type lectins recognize phosphorylated mannose residues, such as mannose-6- phosphate (M6P).140 The first candidate (~275 kDa) receptor (CI-MPR) was found to bind M6P in the absence of cations. Certain cells portray another receptor (CD-MPR) of approximately 45 kDa, which requires divalent cations for optimal binding.25 The larger receptor (CI-MPR) binds with highest affinity in a 1:1 stoichiometry to glycans carrying two M6P residues. The smaller receptor (CD-MPR) has only one binding site for a single M6P. The P-type lectins play an essential role in the generation of functional lysosomes within cells of higher eukaryotes by directing newly synthesized lysosomal enzymes bearing the M6P signal to lysosomes.140
1.3.1.4. Other lectins
The R-type lectins are members of a superfamily of proteins, all of which contain a CRD that is structurally similar to the CRD in ricin. Ricin was the first lectin discovered and it is the prototypical lectin in this category.25 R-type lectins are present in plants, animals, and bacteria and the plant lectins often contain a separate subunit that is a potent toxin. All of the subunits are
N-glycosylated and usually express oligomannose-type N-glycans. The R-type lectin domain is found in several animal lectins, including the mannose receptor (MR) family, and in some invertebrate lectins. Some proteins with the R-type lectin domain are also enzymes and these are found in both animals and microbes.25
The I-type lectins are glycan-binding proteins that belong to the immunoglobulin superfamily (IgSF), excluding antibodies and T-cell receptors.141 There are I-type lectins recognizing sialic acid, other sugars and glycosaminoglycans. The Siglec family of sialic acid- binding lectins is the only well-characterized group of I-type lectins, and roughly more than 500 proteins belong to the IgSF family, according to analyses of mammalian genome prediction.25
Members of this family contain at least one immunoglobulin (Ig)-like fold, made up of antiparallel
β-strands organized into a β-sandwich containing 100-200 amino acids and usually stabilized by an intersheet disulfide bond. Three types or “sets” of Ig domains have been defined on the basis of similarities in sequence and structure to the domains of antibodies: the V-set variable-like
24 domain, the C1- and C2-set constant-like domains, and the I-set domains that combined features of both V- and C-set domains.25 Immunoglobulins can recognize oligosaccharides with a high degree of structural specificity.110
1.4. Lectin-carbohydrate interactions: towards therapeutic and diagnostic applications
Carbohydrate recognition research impacts essentially all areas in which carbohydrates play a role. Examples include (1) infectious diseases, (2) cancer, (3) inflammation and immune responses, (4) signal transduction, (5) stem cell transformation, (6) embryo development, and (7) cardiovascular diseases.17,40,114 Lectins function in every organism to recognize and interact with specific glycan structures.142 The idea that lectins and carbohydrates are excellent candidates as cell recognition markers originates from the findings that both classes of compound are commonly present on the cell surface and that sugars possess tremendous coding capacity.58
The glycan-binding ability of lectins makes them potentially useful as analytical reagents to detect specific glycan structures in biological samples,143 and many lectins have been used for that purpose.142 The ability of lectins to distinguish between subtle variations of oligosaccharide structure makes them perfectly suitable as decoders for such carbohydrates-encoded information. In other words, whilst sugars are able to carry the biological information, lectins are capable of deciphering this “glycocode”. The enormous development of the possibility to inhibit, activate or exploit protein-carbohydrate interactions could bring, especially in medicinal chemistry, the study of lectins and carbohydrates to the forefront of research.58
In contrast to other methods for analyzing glycans such as chromatography, mass spectrometry and enzymatic digestion, lectins can provide precise measurements of specific structures from minute quantities of biological sample.142 This capability is important for distinguishing changes in glycan structures between different tissue samples, which is fundamental to understanding the involvement of particular glycans in disease progression.144
Lectins have been used successfully in a wide variety of formats4,103,145-149 to characterize both normal and pathological glycosylation. Effective therapies typically capitalize on differences between diseased and healthy tissues that can be targeted with drugs. The availability of novel
25 molecular targets that distinguish diseased from healthy cells could vastly amplify therapeutic opportunities.30 In addition, there is an opportunity for the development of non-invasive diagnostics that might identify sites of chronic inflammation prior to the presentation of disease symptoms.30
For successful therapy, early diagnosis of cancer plays a key role.48 Implementation of early detection in traditionally used clinical methods is necessary for significant reduction of the morbidity and mortality caused by cancer.150 For decades, microscopy of biopsy samples was the principal diagnostic method. However, this method suffers from subjectivity and a limited ability to detect the early events of cancer.151 To fulfill the demand for the earliest possible diagnosis, new tools have to be found and applied. It is well known that when a tumor is detected, certain changes at the molecular level have already occurred. The main goal of the new diagnostic approaches is to recognize these changes as early as possible. This recognition can be based on a specific interaction of diagnostic agents with suitable molecular partners, i.e., cancer biomarkers152,153 (e.g., saccharides), represent molecular signatures of the cell phenotype.116
They can be used for specific detection and recognition of particular cell types, such as cancer cells. In addition, biomarkers can be used for prediction of disease progress for chosen and optimized therapy.30,142,154
1.5. Cancer-associated changes in glycosylation
Cancer associated changes in glycosylation include both the under- and overexpression of naturally occurring glycans.155 In research and clinical practice, genomic, proteomic, and metabolomics methods are usually used as methodological approaches for cancer studies.156
Effective diagnostic methodology requires determination of more biomarkers by a different diagnostic method.157 Therefore, the identification of new cancer markers and the development of methods for their selective recognition and determination are intensively sought.48 Besides the methods mentioned above, there is a new emerging field of glycomics research,5 which can be a useful tool for cancer diagnosis and a good starting point for the development of a controlled and targeted drug delivery system.158 In glycomics,5,159,160 cancer recognition is focused on saccharide patterns of cancer cells.161,162 It is well known that the saccharide substitution pattern of cell
26 receptors is significantly changed during oncogenic transformation.162 Such a change was observed in various stages of many cancer types and provides important information about cancer progress, immune response, drug resistance, metastatic capacity, and malignancy. It includes overexpression of the cell-surface polysaccharides,163,164 and oligosaccharides,165,166 and modification of the surface receptors. Two principal mechanisms are known for the tumor- associated alteration of carbohydrate determinants,116 so-called incomplete synthesis and neosynthesis of carbohydrate determinants.167,168 The concept of neosynthesis refers to cancer- associated induction of certain genes implicated in the synthesis of carbohydrate determinants.116
Induction of sLex expression on adult T-cell leukemia cells by the Tax protein is a typical example of neosynthesis.116 On the other hand, the synthesis of complex carbohydrate determinants, well- developed on normal epithelial cells, tends to be impaired upon malignant transformation, predisposing cells to express less complex carbohydrate determinants. The truncated-branched
MUC1 glycopeptide is a typical example for this process.116 Generally, the incomplete synthesis mechanism applies to early stage cancers, while neosynthesis applies to advanced-stage cancers.
1.6. Research goals
The importance and ubiquity of lectins has fuelled strong interest in mimicking their action.20 Synthetic lectins have potential (1) as models for natural lectins, in mechanistic and other fundamental studies, (2) as complementary alternatives to natural lectins in glycobiological research, (3) as diagnostic tools in medicine, and (4) as pharmaceuticals, based on the disruption of natural carbohydrate recognition.154 The chemical structure of a large percentage of modern drugs, particularly those in preclinical and clinical phase, is based on biological building blocks, the peptides and proteins, simple and complex carbohydrates, nucleotides and nucleosides, and lipids.169 The biological system has a special protection mechanism, so all these compounds have usually serious delivery and stability problems. Many peptides, for example, have been identified as potential therapeutics to cure a variety of diseases; however, the progression of these compounds into clinical therapy is thwarted by the persistent hurdles of poor oral
27 absorption and the rapid enzymatic degradation in the body. The development of a practical, economical, and universally applicable system for the delivery of peptide-based therapeutics is, therefore, highly sought after and also of increasing economic and medical significance.169
Given that lectins themselves are peptides, it makes sense to consider peptidic structures for synthetic carbohydrate receptors.20,170 Indeed, a number of biochemical groups have reported on medium-length carbohydrate-binding peptides, discovered by studying fragments of lectins or by selection from phage-displayed,171,172 biopanning method173 and combinatorial libraries,136,174,175 as well as peptide microarrays.176 The 20 canonical α-amino acids constitute the fundamental set of building blocks necessary for human ribosomal synthesis of the major class of biopolymers comprised of proteins and peptides. In traditional medicinal chemistry, this class of compounds has not been considered suitable for drug development in the past, due to susceptibility to proteolytic degradation in cellular environments and often poor cell permeability properties. Nevertheless, recent tendencies in the pharmaceutical industry have revealed an increased interest in the development of so-called biologics. With the recent addition of new technologies, peptides now have the potential of taking a leading role in the discovery and development of new drug candidates. It has been demonstrated that potent peptides can be identified, engineered to have long plasma half-lives and, in at least some cases, have low immunogenicity. As these key issues have been with well-validated technologies, therapeutic peptides are becoming increasingly attractive for the discovery and development of a new generation of drugs.177 This may, at least in part, be due to the successful approval and marketing of several monoclonal antibodies as therapeutics during the past decade,178 as well the reinvestigation of current drug leads that fit between low and high molecular weight extremes, making them attractive structures that can combine both the advantages of small-molecules
(such as higher affinity/specificity to target and lower toxicity profiles, cost, conformational restriction, membrane permeability, metabolic stability) with those of proteins (natural components, target specificity, high potency).177,179-181
Natural products are a very important source of biologically active compounds or lead structures for the development of new drugs. This dissertation focuses on three main research
28 goals involving cell-surface lectin-glycan interactions. The first research goal involves the thermodynamic binding studies of MUC1 derived glycopeptides to galectin-3 as potential inhibitors of the lectin and its role in metastasis. Structural changes on the peptides, such as position of the carbohydrate and type of carbohydrate were assessed in order to elucidate the minimum and maximum binding affinity for galectin-3. In addition, human galectin-3 as well as the galectin-3 carbohydrate recognition domain (CRD) (gal3C) was expressed and purified for binding profile assessment of the glycopeptides.
The second focus in this research has been with a particular peptide, odorranalectin
(OL), mainly because of its unique small-lectin structure and selectivity towards L-fucose. The second research goal of this dissertation was the Fmoc solid-phase syntheses for preparation of
OL and its analogues, as well as the evaluation of their lectin binding profiles. Furthermore, these synthetic peptides were evaluated for toxicity towards human cells, as well as their lectin-binding capabilities towards cancer and healthy cell lines in order to elucidate their potential tools for cancer biomarker detection or targeted drug delivery and therapeutics.154,182,183
The third research goal within this dissertation explores the use of OL as potential delivery vehicle for direct nose-to brain delivery of drugs. This synthetic peptide was evaluated by in vivo intranasal administration to mice, and the presence of the peptides in the brain was examined by mass spectrometry.
29
CHAPTER 2
THERMODYNAMIC ASSESSMENT OF MUC1-TYPE GLYCOPEPTIDES
AND ITS EFFECT ON GALECTIN-3 BINDING
2.1. Overview
The fact that the glycan component of cellular glycoconjugates stores biological information, embodied by the term ‘sugar code’, has attracted increasing attention to analyzing glycan-lectin interactions. The discovery of diverse biological roles for oligosaccharides and glycoconjugates is fueling interest in the development of chemical tools that block their formation and/or function. Two general types of inhibitors are being sought: those that block glycoconjugate biosynthesis and those that interfere with glycoconjugate recognition.24 Effective inhibitors of various biosynthetic steps in glycoconjugate assembly have the potential to transform our understanding of carbohydrate function. Bly blocking the production of specific glycoconjugates, their biological roles can be ascertained.184 Similarly, inhibitors that prevent glycoconjugate recognition can illuminate the function of the natural interactions.185
2.2. Galectin-3
Among lectins, the family of galactose-binding lectins (galectins) has also been recognized as “decoders” of biological information. Through the highly selective choice of binding partners galectins can modulate a variety of cellular functions. The galectin family of lectins plays a significant role in biological processes.186-189 Although the presence of β-linked galactose is an essential for all galectins’ binding, different members of the family exhibit considerable variations in their glycan specificity.190 Among the galectin family members, chimera-type galectin-3 is of particular interest due to its expression in various tissue and cell types, and is found in the nucleus and cytoplasm or secreted in the extracellular space.191 Galectin-3 is monomeric with
30
CRD in the C-terminal region, a collagen-like sequence, and an N-terminal region containing sites for serine and tyrosine phosphorylation.192-196 Galectin-3 can self-associate non-covalently to form homodimers and homopentamers leaving the CRD accessible for binding (cross-linking) with multiple glycoconjugate ligands on the cell surface,197 thereby initiating transmembrane signaling events and affecting various cellular functions.198-200 The N-terminal domain of galectin-3 plays an important role in polyvalent binding to its ligands.201 Considering the galectin-3 role in inflammation, immunity, and cancer,124,198,202 it is not surprising that in the past, a great deal of research has been undertaken to investigate the mechanism of molecular recognition of natural glycan ligands.203-209
2.3. The Thomsen-Friedenreich antigen (TF) and its role in cancer
Understanding the molecular underpinnings of cancer metastasis is an important goal of modern cancer research.138 Metastasis is a multistep process involving many cell-cell and cell- extracellular matrix interactions.210-212 Whereas the initial step of metastasis includes detachment of malignant cells from the primary tumor and migration into the circulatory system, subsequent steps involve malignant cells adhering to each other (homotypic aggregation) or to host cells
(heterotypic adhesion) to form multicellular aggregates.138 It has been suggested that tumor cell adhesion is, in part, mediated by specific interactions between cell surface lectins and carbohydrates present on glycoproteins, glycoplipids, and glycosaminoglycans.210,212-214 One such cancer-associated carbohydrate antigen, the Thomsen-Friedenreich (TF) antigen,209,215 contains the terminal carbohydrate moiety Galβ1→3GalNAc216 (Figure 8),113,116 and although present on most tissues, the TF antigen is masked covalently or structurally on the surface of healthy cells, and is exposed on the outer surface of membranes of human breast carcinomas131,217 and T cell lymphomas.137,216 These properties make the TF antigen of paramount interest for the study of carbohydrate-peptide interactions rendering it an attractive molecule in the development of tumor diagnostic and therapeutic agent.30
31
Figure 8. Structure comparison on the Tn, sTn and TF antigens.113,116
Despite TF antigen alone binds weakly to galectin-3,209 the recognition of TF antigen of cancer-associated MUC1 by galectin-3 promotes cancer cell invasion and metastasis.138 A common feature of cancer cells is that their glycan profile is altered. While mostly serving as biomarkers currently, it is an open question whether such changes have a functional meaning.
Therefore, knowledge of tumor saccharide pattern can be exploited for the development of diagnostic methods and targeted anticancer systems.48 Focusing on the cell membrane mucin
MUC1, increased expression and altered density of shorter glycoforms such as O-linked N- acetylgalactosamine (Tn), sialic acid capped Tn (sTn), and TF antigen are observed changes in malignant and premalignant epithelia. A dynamic binding mode for the TF antigen−galectin-3 complex consisting of two poses has been deduced (Figure 9),209 indicating that the peptide scaffold presenting TF antigen could be relevant for binding and thus provides a possible route for the design of galectin-3 inhibitors with improved affinity and selectivity.209,218
32
Figure 9. Two poses for the TF antigen bound to galectin-3 in the NMR consistent trajectory of the manually docked ligand: (A) pose 1 and (B) pose 2.209
Binding inhibition studies have suggested that 4-OH and 6-OH of the galactopyranosyl ring and 3-OH of the glucopyranoside ring in lactose (Lac) and lactosaminoglycans are primarily responsible for interactions with galectin-1 and -3.219-221 Previous studies220,222 have shown the importance of an axial configuration of the hydroxyl group at the C4 position of the sugar in the binding interaction with gelactin-3. This, in turn, suggests that the combining site specifically accommodates a terminal nonreducing galactose (Gal).223 The crystal structures of the CRD of galectin-3 complexed with lactose and LacNAc demonstrated that Glu165, Arg186, Glu184,
Arg162, Asn160, Asn174, Arg144, and His158 of galectin-3 made contacts with lactose and
LacNAc (Figure 10).224
33
Figure 10. Human galectin-3 carbohydrate binding site interacting with the bound LacNAc moiety. (W1-W3: water molecules, H-bonds: dotted lines).224
225 -1 ITC studies show a Ka of 1160 M and ΔH -4.8 kmol/mol for lactose. LacNAc possesses a 7-fold higher affinity than lactose for galectin-3 and a ΔH that is -3.3 kmol/mol of more favorable than that of lactose.223,225 These results appear to be due to the acetamide group of GlcNAc that makes favorable contacts with Glu165 of the protein via a water molecule, in addition to the hydrogen bonds established by the Arg162 and Glu184 with O3 of GlcNAc.226 The glycan chains of many naturally occurring glycoproteins often possess multiple copies of the same carbohydrate epitope.2 One effect of this carbohydrate polyvalency is to increase the affinity of a glycoprotein for specific carbohydrate binding receptors, including lectins.10,227
Asialofetuin (ASF) possesses three N-linked triantennary chains with nine terminal LacNAc residues that are available for binding to LacNAc specific lectins, including the galectins,2 since it is a naturally occurring polyvalent glycoprotein that induces homotypic aggregation of tumor cells in the presence of certain galectins.228 ITC binding data229 shows that ASF binds to the galectins and two truncated forms 50-80-fold greater than that of LacNAc (Table 2),229 indicating negative cooperativity , whereby the first LacNAc epitope of ASF binds with approximately 6000-fold higher affinity than the last epitope, indicating that the Ka values are independent of the quaternary
34 structures of the galectins. Thus, the microscopic binding constants of the galectins for the first epitope(s) of ASF are in the nanomolar range, with a gradient of decreasing binding constants of the remaining epitopes.229
Table 2. Thermodynamic parameters for binding of ASF to the human galectins.229
a b c d Ka -ΔG -ΔH -TΔS e -4 -1 n (X10 M ) (kcal/mol) (kcal/mol) (kcal/mol) galectin-1 ASF 56.0 7.9 43.0 35.1 0.12 LacNAc 1.0 5.5 8.6 3.1 1.00 galectin-2 ASF 140.0 8.4 46.0 37.6 0.12 LacNAc 1.8 5.8 8.9 3.1 1.01 galectin-3 ASF 140.0 8.4 62.0 53.6 0.11 LacNAc 1.8 5.8 8.9 3.1 1.01 galectin-3 CRD ASF 63.0 7.9 52.0 44.1 0.12 LacNAc 1.1 5.5 10.1 4.6 1.03 galectin-4 ASF 22.0 7.3 38.0 30.7 0.13 LacNAc 0.35 4.8 9.7 4.9 0.97 galectin-7 ASF 30.0 7.5 44.0 36.5 0.12 LacNAc 0.42 4.9 11.2 6.3 0.98
The most commonly used methods to study the binding affinity of galectins for natural and artificial saccharides, and glycoconjugates are isothermal titration calorimetry (ITC),229 solid- phase enzyme linked immunosorbent assay (ELISA) assays,230 surface plasmon resonance
(SPR),215 frontal affinity chromatography,190 microscale affinity chromatography coupled to mass spectrometry,231 and fluorescence polarization.232 However, none of these methods, with exception of fluorescence polarization, is simple and amenable to rapid high throughput processing of a large number of samples. The glycan-microarrays have received much attention recently since they permit high-throughput analysis and require the very small amounts of glycans.233 In order to achieve tight binding, the ligand density and presentation of glycans on arrays are of crucial importance. The binding specificities of many lectins have been evaluated using this technology.234-236 Recently, a high-throughput screening (HTS) amenable assay was developed based on AlphaScreen technology for the discovery of inhibitors of galectin-3.237
35
2.4. MUC1 glycopeptides
It has been suggested that natural polyvalent ligands, such as mucins, may use variations in binding site density to modulate biological interactions and the responses that result.238,239 Mucins are predominant glycoproteins found in gastrointestinal (GI) epithelia, and their structures differ according to the location in the GI tract and the state of cellular differentiation.80 The mucins act as ligands for targeting of leukocytes to endothelial cells.240 The dominant structural feature of mucins is their high content of carbohydrate determining the high molecular weight of mature mucins and a large part of their physicochemical properties. Epithelial cancer cells often overexpress mucins that are aberrantly glycosylated.241,242 Altered mucin glycosylation leading to shorter carbohydrate side chains of altered sialylation has been observed frequently associated with many pathological conditions,243 including cancer.40,244-246 Because cell surface carbohydrate epitopes are not only considered as markers reflecting e.g. the degree of differentiation but have a functional dimension by serving as docking sites for endogenous receptors,247 a systematic study on mucin-presented sugars, in terms of structure and mode of presentation (site and density), is warranted.
MUC1 is a large transmembrane O-glycoprotein. More specifically, MUC1 contains a 20- mer peptide with the following sequence: HGVTSAPDTRPAPGSTAPPA, a tandem repeat domain of the mucin-type glycoprotein coded by the muc-I gene.248,249 These sites are subject to
O-glycosylation that contributes to form a structure that extends beyond the glycocalyx of the cell.250 Overexpression, aberrant intracellular localization, and changes in glycosylation of this protein was found in most human carcinomas, confers anchorage-independent growth and tumor proliferation.250,251 Several lines of evidence point towards a biological role of MUC1 in colorectal cancer (CRC) and esophageal cancer, more specifically, a positive correlation between secretion, proliferation, invasiveness, metastasis and bad prognosis. MUC1 appears thus a good therapeutic target to slow down tumor progression.252
36
2.5. Peptide modification by glycosylation
An increased interest in the development of peptide drugs as potential drugs within the last decade has resulted in the search for new ways to prolong and/or enhance the biological activity of the peptide drug at the target site.169,253-256 However, this has been a persistent challenge to pharmaceutical scientists because of several unfavorable physicochemical properties including susceptibility to enzymatic degradation, low lipophilicity, the lack of specific transport systems to direct such peptide drugs into cells or across the blood brain barrier and the high conformational flexibility. Based on the positive effects that glycosylation makes on some properties of synthetic peptides, it is not surprising that incorporation of glycans into key positions of the peptide chain has become one of the most effective strategies to overcome the drawback of peptide drugs.169,253,257 Glycosylation has also been explored as a tool to modify the biological activity of peptides.258 It has been observed that attachment of carbohydrate residues to peptides, even to ones that are not glycosylated in nature, can influence their biological functions.254,259-261
The conjugation of carbohydrates to peptides provides many potential benefits, including (1) the ability to alter the physicochemical properties of peptides (e.g. improving their water solubility260,262-265 and peptide conformation,266-272 (2) the possibility of improving their enzymatic stability,260,273-278 (3) to enable their transport across physiological barriers via specific transporters,279-286 and (4) to allow for their targeting to specific carbohydrate-recognition receptors (e.g. lectins), and this could form basis of cell or organ-specific targeting.275,287,288
Glycosylation appears to modulate in vivo efficacy of protein drugs by altering the balance between their potencies (PD-pharmacodynamics) and exposure time (PK- pharmacokinetics). Changes to protein PK parameters induced by glycosylation include improved absorption and distribution, longer circulation lifetimes, and decreased clearance rates. However, many aspects regarding the mechanisms by which glycosylation induces such effects remain unclear. In addition, it is not well understood how the density, type, size, and charge of glycans affect the overall protein physicochemical and pharmacological properties.273,289,290
To assess the potential of the peptide portion to be located in the direct vicinity of the core 1 disaccharide in binding affinity with galectin-3, a threonine residue attached to the glycan
37 moiety was used in our study. Previous monitoring of glycopeptides and glycan derivative libraries has indicated a possibility for peptide−aglycone interactions.291-293 Given the evidence that the human lectin galectin-3 can interact with mucins and also weakly with free TF antigen, we have initiated the study of interaction of MUC1 (glyco)peptides (Scheme 1) with this endogenous lectin.
Scheme 1. The TF-glycosylated MUC1-peptides used in this study.
2.6. Thermodynamic assessment study
2.6.1. Assessment of binding interaction of glycosides with galectin-3
As a comparison between galectin-3 and glycopeptide vs. carbohydrate behavior, we first conducted ITC binding studies with full-length galectin-3 and Thomsen-Friedenreich (TF) glycan
(Figure 11 A) and TF-αThr conjugate (Figure 11 B), respectively. The obtained Kd values for the full-length galectin-3 and TF (Kd = 245 µM; Figure. 11 A) and TF-αThr conjugate (Kd = 288 µM;
Figure 11 B) were in a similar range (µM) but slightly lower, to those reported in literature.294 In order to exclude the effect of the galectin-3 N-terminal domain in binding we also performed binding studies with the galectin-3 CRD. The Kd values obtained for the TF-αThr conjugate (Kd =
272 µM; Figure 11 C) is comparable to the binding affinities of the full-length galectin-3 (Kd = 288
µM; Figure 11 B).
38
39
Figure 11. ITC titration profile for galectin-3/galectin-3 CRD with tumor-associated antigens. (A) galectin-3 (140 µM) with TF (Galβ1-3GalNAc) (2.6 mM); (B) galectin-3 (140 µM) with TF-αThr (3 mM) and (C) galectin-3 CRD (250 µM) with Thr-αTF (3 mM). The top panel shows the experimental ITC data and bottom panel shows a fit to one-site model of the binding data using MicroCal analysis software (Origin 7.0). The best values for the stoichiometry (n), binding affinity (Ka), dissociation constant (Kd), enthalpy (ΔH), and change in entropy with respect to temperature (TΔS) are shown in the graph below.
2.6.2. Assessment of binding interaction of glycopeptides with galectin-3
The biding affinities of the glycosylated MUC1 fragments that carry TF antigen (Scheme
1), for galectin-3 were assessed by ITC (Figure 12). The measured Kd for galectin-3 and
4 9 glycosylated MUC1-Thr (Kd = 28 μM; Figure 1 2B), MUC1-Thr (Kd = 45 μM; Figure 12 C), and
16 MUC1-Thr (Kd = 45 μM; Figure 12 D) were 6-10x higher in comparison to TF glycan alone (Kd =
288 μM; Fig.12 A) and comparable to the natural ligand epitope LacNAc (Kd = 33 μM; Figure 12
A). No binding was observed for the non-glycosylated control version of MUC1 peptide (data not
237 shown). Interestingly, the measured Kd for galectin-3 and glycosylated serine analogue, MUC1-
5 4 Ser (Kd = 63 μM; Figure 12 E), is slightly lower than its threonine analogue, MUC1-Thr (Kd = 28
μM; Figure 12 B). Analysis of the binding affinity of galectins-3 for the truncated glycopeptides
4 4 show that measured Kd’s are slightly lower when compared to MUC1-Thr Thr (Kd = 28 μM;
4 4 Figure 1 2B); and for MUC11-15-Thr (Kd = 132 μM; Figure 12 G), and MUC11-8-Thr (Kd = 346 μM;
4 Figure 12 F), the Kd were 5x and 12x lower in comparison to MUC1-Thr , respectively.
In order to explore the effect of the galectin-3 N-terminal domain in binding, we have also performed binding studies with the galectin-3 CRD (Figure 13). The Kd values obtained for
LacNAc (Kd = 30 µM, Figure 13 A) was unaffected, while the affinity of the glycosylated MUC1-
4 9 5 Thr (Kd = 94 μM; Figure 13 B), MUC1-Thr (Kd = 103 μM; Figure 13 C) and MUC1-Ser (Kd = 103
μM; Figure 13 D), was slightly lower compared to the binding affinities of the full-length galectin-3.
40
41
Figure 12. ITC titration profile of galectin-3 with LacNAc and MUC1-type glycopeptides. (A) galectin-3 (140 µM) with LacNAc (2.6 mM), (B) galectin-3 (280 µM) with MUC1-Thr4 (2.4 mM), (C) galectin-3 (280 µM) with MUC1-Thr9 (2.0 mM), (D) galectin-3 (280 µM) with MUC1-Thr16 5 4 (3.0 mM), (E) galectin-3 (280 µM) with MUC1-Ser (3.0 mM), (F) galectin-3 (280 µM) with MUC11-8-Thr (3.0 mM), and (G) galectin-3 (280 4 µM) with MUC11-15-Thr (3.0 mM). The top panel shows the experimental ITC data and bottom panel shows a fit to one-site model of the binding data using MicroCal analysis software (Origin 7.0). The best values for the stoichiometry (n), binding affinity (Ka), dissociation constant (Kd), enthalpy (ΔH), and change in entropy with respect to temperature (-TΔS) are shown in the graph below.
42
Figure 12. ITC titration profile of galectin-3 with LacNAc and MUC1-type glycopeptides. (E) galectin-3 (280 µM) with MUC1-Ser5 (3.0 mM), (F) 4 4 galectin-3 (280 µM) with MUC11-8-Thr (3.0 mM), and (G) galectin-3 (280 µM) with MUC11-15-Thr (3.0 mM). The top panel shows the experimental ITC data and bottom panel shows a fit to one-site model of the binding data using MicroCal analysis software (Origin 7.0). The best values for the stoichiometry (n), binding affinity (Ka), dissociation constant (Kd), enthalpy (ΔH), and change in entropy with respect to temperature (-TΔS) are shown in the graph below.
43
Figure 13. ITC titration profile of galectin-3 CRD with LacNAc and MUC1-type glycopeptides. (A) galectin-3 CRD (140 µM) with LacNAc (2.6 mM), (B) galectin-3 CRD (280 µM) with MUC1-Thr4 (2.4 mM), (C) galectin-3 CRD (280 µM) with MUC1-Thr9, (D) galectin-3 CRD (280 µM) with MUC1-Ser5 (3.0 mM). The top panel shows the experimental ITC data and bottom panel shows a fit to one-site model of the binding data using MicroCal analysis software (Origin 7.0). The best values for the stoichiometry (n), binding affinity (Ka), dissociation constant (Kd), enthalpy (ΔH), and change in entropy with respect to temperature (-TΔS) are shown in the graph below.
2.7. Discussion and conclusions
The binding affinities of the glycosylated MUC1 peptides for galectin-3 were assessed by
ITC. The significant difference in the thermodynamic profiles of LacNAc and MUC1 glycopeptides binding to galectin-3 (Figure 14 A) and gal3C (Figure 14 B) was also observed. The LacNAc binding was driven by enthalpy contributions (ΔH = -12.74 kcal mol-1), in agreement with the widely held view that interaction between lectin and carbohydrate ligands are characterized by favorable enthalpic contributions counteracted by an unfavorable entropy.223,295,296 The measured binding constants for galectin-3 and glycosylated MUC1 fragments by ITC were comparable to
LacNAc and 10 x higher in comparison to TF glycan alone. No binding was observed for the non- glycosylated control version of MUC1 peptide. The most notable feature of the MUC1-Thr4 and
MUC1-Thr9 binding to galectin-3 was the shift from the favorable enthalpy towards the entropy driven binding interaction. The small enthalpy contribution to the association free energy (G) was compensated by gain in entropic contribution. This might suggest that the presentation of the carbohydrate ligand by the natural peptide scaffold leads to more favorable entropy changes upon binding. Several studies have indicated that protein conformational entropy, besides the hydrophobic effects and solvation, can contribute significantly to the free energy of ligand binding.297-300
44
Figure 14. Thermodynamic profiles of galectin-3 and galectin-3 CRD with carbohydrates and MUC1-type glycopeptides. (A) Thermodynamic signature of full length galectin-3 binding to LacNAc, Thr-αTF, and glycopeptides. (B) Thermodynamic signature of galectin-3 CRD binding to LacNAc, Thr-αTF, and glycopeptides.
Recently, it has been shown that ligand binding significantly affects the conformational entropy of galectin-3301 and galectin-1.302 It was speculated that lectins use this fine-tuning mechanism to compensate for the low binding affinities for carbohydrates.301 Our results with
MUC1 glycopeptides further support this idea and suggest that the higher affinity may result from the synergy of favorable enthalpic and entropic contributions to the binding affinity. Based on the determined interaction from thermodynamic and structural studies, it can be shown that the contact between the lectin and glycopeptide not only involved the carbohydrate residue, but also the peptide backbone. Thus, presentation of the carbohydrate ligand by the natural peptide
45
scaffolds is highly relevant in binding interactions and should not be overlooked when studying glycan–protein interactions.42 In addition to the glycan presentation, the density patterns of O- linked glycans can have a major impact on recognition. Better understanding of this process, that combines contribution of protein and glycan component, is essential for studying the functional relevance of tumor-associated carbohydrate antigens (TACAs) on MUC1.
2.8. Materials and methods
2.8.1. Chemicals and instrumentation
ASF, LacNAc, IPTG, BME and lactose were purchased from Sigma-Aldrich (St. Louis,
MO). All solvents were purchased from Fisher Scientific (Atlanta, GA) or Sigma–Aldrich, and were analytical reagent grade or better. Branson digital sonifier was purchased from Emerson
(Danbury, CT). NanoDrop spectrophotometer was purchased from Thermo Scientific (Waltham,
MA). iTC200 was purchased from MicroCal, LLC (Worcestershire, UK).
2.8.2. Bacterial strains and reagents
General reagents for microbiology, protein expression and purification work were purchased from Fisher Scientific (Pittsburgh, PA). Microbial strain E. coli Rosetta (DE3)_pLysS competent cells from EMD4Biosciences (Billerica, MA). Dehydrated culture media and agar, and polystyrene plates used for protein expression were purchased from BD (Franklin Lakes, NJ).
Control antibiotics, -lactose agarose resin and BME were purchased from Sigma-Aldrich (St.
Louis, MO). Amicon Ultra centrifugal filters with MWCO 10,000 were purchased from Millipore
(Billerica, MA). SDS-PAGE pre-made gels and SimplyBlue Safe Stain was purchased from
Invitrogen (Grand Island, NY).
2.8.3. Galectin-3/Gal3C expression and purification
Recombinant galectin-3 expression and purification.237 The open reading frame (ORF) of the human galectin-3 gene_LGALS3_(NM_002306.1) was amplified by PCR, using primers set introducing NdeI and HindIII restriction sites and a stop codon. The amplified fragment was ligated
46
into pET-26b(+) (Novagen), allowing expression of recombinant galectins-3 (LGALS3) in the absence of N- and C-terminal tags.237 The protein expression was carried out in E. coli Rosetta
(DE3)_pLysS competent cells. The transformed cells were grown in LB medium in the presence of kanamycin (50 µg/mL) and chloramphenicol (34 µg/mL). Recombinant protein was expressed according to the manufacturer’s protocol. Briefly, E. coli culture was grown at 37°C until the OD600 of
0.6 was reached. The induction was performed by adding IPTG to the final concentration of 0.5 mM and the incubation was continued for 4 h at 30 °C. Cells were harvested by centrifugation (3,500 x g,
20 min) at 4°C and the cell pellet was stored at -80°C. The cell pellet was re-suspended in phosphate buffer (75 mM Na2HPO4/KH2PO4, 2 mM EDTA, 4 mM BME, pH 7.2), and sonicated using Branson digital sonifier (30% intensity) 4 times for 30 s on ice. After centrifugation at 4°C (16,000 x g, 15 min), the supernatant was then applied to a -lactose agarose resin. Galectin-3 was eluted from the affinity column with 200 mM lactose, extensively dialyzed (for 4 d) against phosphate buffer (10 mM, 50 mM
NaCl, 4 mM BME, pH 7.5) at 4°C to allow complete removal of lactose, concentrated by using
Amicon Ultra centrifugal filter (MWCO 10,000) for experimental use. About 80 mg of 99% pure galectin-3 was recovered per liter culture. Recombinant galectin-3 purity and integrity was monitored by 10% SDS-PAGE stained with SimplyBlue Safe Stain (Figure 15 A).237 The protein content was determined by using the NanoDrop spectrophotometer at = 280 nm and extinction coefficient
294 reported for galectin-3 (E1% = 6.1).
Recombinant galectin-3 CRD expression and purification.237 The CRD of galectin-3 was obtained by depletion of N-terminal domain (amino acid residues 1-107) of galectin-3.
Recombinant galectin-3 CRD was expressed in E. coli Rosetta (DE3)_pLys and purified in a similar manner as described for full length galectin-3. After dialysis, about 30 mg of 99% pure galectin-3 CRD was recovered per liter culture (Figure 15 B).237 The protein content was determined by using the NanoDrop spectrophotometer ( = 280 nm, extinction coefficient for 1% solution = 6.8).303
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Figure 15. SDS-PAGE of A) galectin-3 and B) galectin-3 CRD.237
2.8.4. Isothermal titration calorimetry measurements
Calorimetric measurements were recorded using an iTC200 calorimeter. In brief, a solution of 40 μL of the ligand, at a concentration 10-fold greater than that of galectin-3, was titrated in aliquots of 1 μL into the calorimetric cell at 1000 rpm, containing 203 μL of galectin-3 (full-length or CRD). Both, ligand and galectin-3 were prepared in exactly the same buffer containing 20 mM phosphate, 0.15 M NaCl, 10 mM BME, pH 7.2. Injections were performed every 240 s at 25°C. A titration of each glycan in the sample cell containing only buffer was subtracted from the actual binding experiment before data analysis. The thermodynamic analysis was performed using the
MicroCal analysis software (Origin 7.0).
48
CHAPTER 3
STRUCTURAL MODIFICATION
OF NATIVE ODORRANALECTIN (OL) PEPTIDES AND ITS EFFECT ON
STABILITY, L-FUCOSE BINDING AND HUMAN CELL TOXICITY
3.1. Overview
Adhesion to the glycosylated surface of eukaryotic cells, mediated by lectins for example, plays an important role in inflammation and other cellular processes of living organisms.304,305 To elucidate the mechanisms involved in the adhesion to cell surfaces and their biological consequences, the investigation of the molecular interactions between carbohydrate recognition domains of lectins and their ligands is of relevance.294,295 Involved in most of the cell-cell and pathogen-host adhesion processes are lectins and selectins.36,58 Even in normal, healthy cells, surface carbohydrate structures are known to be characteristic markers for different types of cells.306 The transformation of normal to cancerous cells is often associated with the alteration of cell surface carbohydrates and the expression or over-expression of certain carbohydrates.306
Since cell membranes and extracellular matrix are predominantly composed of glycoconjugates, analysis of cell-surface glycosylation provides information about cell surface glycosylation as their state of differentiation.304 Therefore, many studies using lectins have been used to identify processes governing the metastatic cascade, and thus malignant progression.80,172 This is important because the degree of tumor differentiation has been found to correlate with survival in cancer patients.156,307,308 Therefore, many carbohydrates are considered cancer-associated antigens (CAA) or tumor-associated carbohydrate antigens (TACAs).113,309 In addition, each type of malignant tissue is characterized by a distinct set of changes in glycan expression (Table 3).30
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Table 3. Common expression patterns of cancer glycans on malignant tissues.30,310,311
Cancer Malignant tissue glycan Ovary Pancreas Liver Breast Colon Brain Prostate Skin Lung sLex X X X X X sLea X X X X X Ley X X X X X X TF X X X X sTn X X X X X X Globo H X X X X X X
The overexpression of oligosaccharides, such as Globo-H, Lewisy (Ley), Lewis x (Lex), sLex, Lewis a (Lea), and sLea antigens, is a common feature of oncogenically transformed cells
(Figure 16).30,312-316 Numerous studies have shown that this abnormal glycosylation can promote metastasis,317 and hence the expression of these compounds is strongly correlated with poor survival rates of cancer patients.241 Among all carbohydrate-based CAA, sLex and sLea are of indispensable interest due to their role in cancer120,318,319 (Figure 16).116 It is known that sLea plays a principal role in the adhesion to the endothelium of cancer cells derived from the lower digestive organs, such as the colon and rectum, while sLex determinant was found to figure heavily in the adhesion of breast, ovarian, pulmonary and leukemia cancer cells.120,171,319 With this aberrant glycan expression, “binders” that can recognize these carbohydrates will be very useful research tools, diagnostic agents, and possibly therapeutic agents.17
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Figure 16. Structures of carbohydrate determinants having fucose-binding activity.113,116
One of the most common changes is an increase in the size and branching of N-linked glycans. The increased branching creates additional sites for terminal glycosylation by sialyltransferases and fucosyltransferases, corresponding to altered terminal sialic acid and fucosylated glycans.30 Cell-surface fucosylated carbohydrate chains also provide potential binding sites to endogenous carbohydrate-binding proteins. Changes in carbohydrate expression on tumor cells can alter cell adhesion and may be suitable targets for therapeutic exploitation.80
Since transformed cells show increased sensitivity to lectins,320,321 studies have been performed to examine whether lectins inhibit tumor growth. Several lines of evidence extrapolated from in vitro and in vivo studies suggest that lectins are strong candidates in tumor targeting therapy. The development of molecular tools for cancer diagnosis and prognosis is already in progress and it is still evolving.48,322 Many biomarkers of cancers have been identified.152,322 An ideal recognition preferably employs biomarkers (targets) which are overexpressed on all tumor cells but not on the normal cells, and at the same time are required for cell survival, proliferation, or other critical
51
functions.323 The recognition component of a diagnostic agent can also be used in the drug delivery system to enhance its efficacy of medication.158
3.2. L-fucose and its role in cancer
Among all pathologically relevant glycosylation changes, cancer is probably the most extensively studied.17 Among approximately ten kinds of oligosaccharide modifications,
324 fucosylation is one of the most important types in cancer. α-L-fucose (6-deoxy-L-galactose) is a monosaccharide that is a common component of many N- and O-linked glycans and glycolipids produced by mammalian cells.325 This sugar is enzymatically synthesized in mammalian cells and is also recovered by cells from extracellular sources by a specific transmembrane carrier and intracellular salvage pathway.113 Two structural features distinguish fucose from other six-carbon sugars present in mammals. These include the lack of a hydroxyl group on the carbon at the 6-
326 position (C6) and the L-configuration (Figure 17 B). Fucose frequently exists as a terminal modification of glycan structures; however, recently glycosyltransferase activities capable of adding sugars directly to fucose have been identified.327 Specific terminal glycan modifications including fucosylation (which comprises the transfer of a fucose residue to oligosaccharides and proteins),324 can confer unique functional properties to oligosaccharides and are often regulated during ontogeny and cellular differentiation328,329 (Figure 17 A).330
To date,331 some lectins have been identified as fucose-specific including Lotus tetragonolobus332,333 and Ulex europaeus334 lectins from plants, Anguilla lectin from eel,335 Aleuria aurantia lectin (AAL) from mushroom,336 Rhizopus stolonifer lectin from fungi,337 and Ralstonia solanacearum lectin from bacteria.338 Among these lectins, AAL and R. stolonifer lectin preferentially bind to α(1,6)-fucosylated oligosaccharides, whereas Ulex europaeus and Lotus tetragonolobus lectins prefer α(1,2)-linked fucose residues.339 AAL is a commercially available lectin that is known for its high affinity for α(1,6)-fucosylated glycans, i.e. where a fucose residue is attached to the innermost GlcNAc of the N-linked-core structure represented as
Fucα1→6GlcNAc-R and has weak binding toward fucose in the outer arm such as
Fucα1→2Galβ1→4GlcNAcβ1→R, Galβ1→4(Fucα1→3)GlcNAc→R, and
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Galβ1→3(Fucα1→4)GlcNAc→R, where R = H or sugar,340 therefore, binds preferentially to Fuc
α(1,6)-linked to the proximal GlcNAc of the N-linked glycans, and to terminal Fuc with an α(1,3)- or α(1,4)- linkage in O-glycans,336,341-345 and it is widely used to estimate the extent of α(1,6)- fucosylation (core fucosylation) on glycoproteins and to fractionate glycoproteins,155,341 since AAL itself exhibits broad specificity for α(1,2)-, α(1,3)-, and α(1,4)-fucose-containing oligosaccharides.346 Ulex europaeus (UEA-I) lectin and Aleuria aurantia lectin (AAL). It is generally assumed that AAL has a strong affinity toward core fucosylated glycans, while UEA-I is considered to have high affinity for Fuc with an α(1,2)-linkage.324,333 Although there are many fucose-specific lectins, their cross-reactivity to the linkage of fucose-binding is a problem.324
Figure 17. A) Example of an N-glycan structure containing some of the main carbohydrate alterations found in tumors: β(1,6)-branching, sialylation, core fucosylation, and sialyl-Lewis 330 antigens; B) α-L-fucose and α-D-galactose structure comparison.
Fucosylated glycans have been implicated in the pathogenesis of several human diseases.326 Two prominent examples of altered glycosylation in cancer involve fucose-containing oligosaccharides. First, expression of A and B blood group antigens is lost in many tumors with concominant increases in H and Lewisy expression, changes that correlate with poor clinical prognosis.153,347,348 Second, up-regulation of sLex and sLea (Figure 16) has been demonstrated in numerous cancers, and these increases are also associated with advanced tumor grade and poor prognosis.317-319 Moreover, increased α(1,6)-fucosylation (core fucosylation) of α-fetoprotein is observed in hepatocellular carcinoma patients and is a well-known marker for distinguishing hepatocellular carcinoma (HCC) from chronic liver disease.324,349 In addition, a core-fucosylated
53
N-glycan, CD147, has been recently identified as a novel tumor marker for clinical diagnosis of oral cancer.350,351 Also, site-specific fucosylation has been shown in haptoglobin (Fuc-Hpt), which can be either α(1,2)-, α(1,3)- or α(1,6)-fucosylated depending on the type of cancer.352
Fucose is incorporated into numerous tumor-associated carbohydrate antigens, and appears to have important functional as well as biomarker significance, in common human cancers.113,307,328,353-360 Data suggests that diagnosis and prognosis would be aided by detection of fucosylated molecules in tissue samples. Unfortunately, the names of fucose-containing cancer antigens rarely provide clues that the sugar is, in fact, present. As a result, fucose remains nearly anonymous in the hispathology literature. Why should one be concerned with fucose? Because two established functional roles for fucose are directly relevant to common cancers. First, fucose serves as an interaction domain which mediates cell-cell adhesion, cell-matrix adhesion, and cell- cell signaling. Fucose is often expressed as the terminal sugar on glycoproteins and glycolipids and is thus well-positioned for interactions with the cell’s environment. Fucose’s hydroxyl groups have been shown to ligate calcium enabling homotypic cell adhesion as well as cell adhesion to
(calcium dependent) selectin molecules on endothelial cells. This mechanism serves both normal inflammatory cell recruitment and metastatic adhesion of circulating tumor cells.328 The second major role of fucose is regulation of receptor activity. For example, the Notch signaling controls many cell fate decisions during embryonic life, including laterality and segmentation, as is also critical for maintaining homeostasis in mature cells, and fucosylation of the Notch1 receptor is required for optimal sensitivity to its ligands. “Core fucosylated” glycans regulate the biological functions of integrins and cadherins,304 as well as growth factor receptors such as EGFR and
TGF-β1.361
In fact, α-L-fucose is essential in order to construct first, the malignant and then the metastatic phenotype of many human breast cancers.113 The human breast cancer cell lines
MCF-7 (non-metastatic), T-47D (non-metastatic), MDA-MB-231(metastatic) were found to express the gene for the fucosyltransferase enzyme that completes the synthesis of sLex.113,362,363
In addition, fucosidase (defucosylation) treatment caused extensive changes in the glycan phenotype of MDA-MB-231cells, with significant reductions in adhesive and invasive
54
properties.355,356 Thus, there is clear evidence for the involvement of fucose, as incorporated into
Lewis antigens, in the phenotypic, invasive and metastatic properties of multiple human breast cancer cells in vitro. Multiple well-characterized breast cancer cell lines express these antigens, and sLex is particularly associated with the more invasive and metastatic cell types.364 Needless to say, α-L-fucose is not simple a bystander molecule, but in fact, contributes to many fundamental oncologic properties of breast cancer cells.113 Fucose-related biomarkers in breast cancer are thus known or suspected based on in vitro studies as well as results obtained with patient-derived material.316 Fucosylation of cell surface molecules is unlikely to be a random or fortuitous bystander modification, since functional roles in cell-cell and cell-extracellular matrix interactions have already been documented. The significance of circulating fucosylated glycoproteins remains to be elucidated.113
3.3. Odorranalectin (OL) for potential tumor-targeted therapeutics
Specific changes in glycosylation could be useful as diagnostic tools or for targeted drug delivery in many cancers.30 Optimal delivery systems must be developed in order to maximize clinical benefits and to minimize adverse effects on the host.154 The most considerable challenges facing effective current cancer therapies commonly involve radiation and cytotoxic chemotherapeutic treatment, both of which generate serious systemic toxic side effects.365,366 In addition, another drawback with current cancer therapy is their lack of tumor-localizing and an even distribution throughout the whole body, rendering a prevalence of unrequired dose-limiting toxicity to non-cancerous tissues and organs, which is further compounded by a limited ability to rapidly and easily monitor drug delivery, pharmacodynamics and therapeutic response.366
Considering the tiny tumor burden relative to body weight, most drug molecules are also distributed to nonmalignant tissues upon systemic delivery,154 damaging proliferating cell types of the digestive tract, central nervous system (CNS) and bone marrow, and physiological function of many tissues, resulting in toxicities and impaired organ function.366 Besides, short half-lives and undesirable pharmacokinetics are among the other drawbacks that inhibit effective cancer chemotherapy,365 resulting in extremely inefficient delivery of anticancer drugs to the tumor.316,330
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Application of nanotechnology in drug delivery systems has provided new avenues for engineering materials with molecular precision, by combining diagnostic and therapeutic actions for immediate administration of therapy.367,368 Nanotechnology and hybrid anticancer drugs369 can generate a library of sophisticated drug delivery systems that integrate molecular recognition and site-specific delivery of the therapeutic agent, formulating therapeutic agents in biocompatible nanomaterials such as nanoparticles, nanocapsules, liposomes, micelles and rods.365,366,370
Several fucose-binding lectins have been proved useful as tools in research on human cancers.113,371,372 In cancer, it is evident that to target cells on the basis of their altered glycosylation is a strategy for targeted drug delivery. Odorranalectin (OL) (Figure 18 A) is a 1.7 kDa cyclic peptide consisting of 17 amino acids with the following sequence: YASPK- cyclo(CFRYPNGVLAC)T. The cyclic peptide adopts a β-turn conformationstabilized by one intramolecular disulfide bridge between Cys6-Cys16 and three hydrogen bonds between Phe7-
Ala15, Tyr9-Val13, Tyr9-Gly12 (Figure 18 A).373 Residues Lys5, Cys6, Phe7, Cys16 and Thr17 form the binding site of L-fucose with a binding affinity in the low micromolar range (Kd = 55 μM) (Figure 18
B).373 In addition, OL has very low immunogenicity known to be stable in mice plasma for more than 5 h,373 rendering it an excellent candidate for drug delivery to targeted sites, such as tumor- associated fucosylated antigens implicated in the pathogenesis of several cancers,374-379 for overcoming the nonspecificity of most anticancer agents. Taking into consideration OL’s unique small-lectin structure and selectivity towards L-fucose, we hypothesize that OL can serve as a potential tumor-targeted drug delivery vehicle.
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Figure 18. Key features of OL. A) The mean structure calculated from the 20 lowest-energy structures which highlighted three hydrogen bonds (green broken lines) and one disulfide bond (black solid line; B) Five residues consist of the L-fucose binding site of OL, which were displayed with side-chains in the structure of OL (atoms C, O, N, H, S shown in black, red, blue, light gray and yellow, respectively); C) Electrostatic surface of OL (positively charged region and negatively charged regions are shown in blue and red, respectively).380
In many naturally occurring cyclic peptides, conformational constraints are obtained by a disulfide bridge.381-383 Replacement of the disulfide bridge in these cyclic peptides by an amide bond may lead to analogs with similar conformational constraint,382,384,385 but with different physicochemical properties due to the addition of hydrogen-bonding sites through the lactam bridge and consequent increase of ring polarity.382-384,386-389
Cyclic peptide derivatives, in contrast to their linear peptide counterparts, are interesting lead structures for peptide-based drug development, due to their increased chemical and
57
enzymatic stability, conformation, and improved pharmacodynamic properties.390,391 Notably, intramolecular disulfide bonds play an important role in the folding and stability of many biologically important peptides and proteins, as they serve to covalently crosslink portions of the polypeptide chain that are apart in the linear sequence.384,392-395 To generate more information on
OL’s structural requirements for L-fucose binding, lectin-binding selectivity towards cancer cells and nonselective toxicity, we have synthesized OL and its two amide analogues varying in the direction of the amide bridge (Figure 19 B).178 Because side-chain to side-chain cyclization can be achieved by two approaches differing by permutation of the two residues involved in the lactam bridge, two analogs differing in the orientation of the amide bond were synthesized.389,396
Furthermore, these synthetic peptides were evaluated for toxicity towards human cells, as well as their fucosylated glycan-binding capabilities towards fetuin and asialofetuin (ASF), two models of fucose-containing glycoproteins. In addition, their selectivity towards cancer vs. healthy cell lines was assessed in order to elucidate their potential tools for cancer biomarker detection or targeted drug delivery and therapeutics.154,182,183
We found that substituting the disulfide bridge in the native sequence can result in either complete loss or retain its fucose-binding profile depending on the particular orientation in of the amide bond. Moreover, all peptides showed no toxicity toward human cells. In addition, both native sequence as well as its active amide analog showed binding selectivity on cancer cell- surfaces over healthy epithelial cells in a lectin-binding cell-based assay. These results shed light for further structural optimization including a combinatorial chemistry approach of the native peptide sequence.
3.4. Solid-phase synthesis
Amino acid sequences of the native odorranalectin (OL) with the disulfide bridge as well as its two cyclic peptides analogs with amide substitutions (OLA3 and OLA4) are shown in Figure
19 A. During the past decades, numerous efforts have been made to mimic the intramolecular disulfide bridges in cyclic peptides with other appropriate linkages to examine the effect on their activity in hopes to enhance or at least retain biological activity and selectivity.397-401 Among the
58
numerous disulfide mimicking moieties, amide linkage (lactam) modification is of particular interest due to its easy formation by using the side chains of diaminopropionic acid (Dap)/ lysine
(Lys) in conjunction with aspartic acid (Asp)/ glutamic acid (Glu) to replace the two cysteines needed for one disulfide bridge to form by means of amide bond formation, and therefore achieve cyclization (Scheme 2).385,402-404 Replacement of the disulfide bridge by a lactam bridge brings about two possible orientations of the amide bond (direct and reverse), therefore rendering two possible amide analogs for a single disulfide bridge substitution (Figure 19 B). This can be considered as a partially modified retro-inverso (PMRI) peptide, in which the binding pattern within the specific amide bond is reversed.405 The new amide bond peptide analogs can therefore retain similar characteristics as the parent peptide if the geometrical mimicry of the parent peptide is retained,406,407 or result in a change in the interaction depending on the direction of the amide bond, and thus alter the PMRI peptide’s secondary structure and/or activity, if such particular peptide bond is involved in a functionally significant interaction (e.g. through H-bonding to other groups in the parent peptide or ligand/receptor),408,409 or if the backbone and/or side-chain orientation is severely compromised.405,407
Scheme 2. Possible disulfide bridge replacements used in peptide chemistry.
59
To replace the two cysteine residues in the OL native sequence, an aspartic acid derivative and a diaminopropionic acid derivative were chosen for numerous reasons. First, because they lead to a ring size similar to that formed by the disulfide bridge.389 In addition, because of the similar conformations shown by the molecular modeling simulations done (see section 3.5.2.), and also for synthetic modifications suitability, especially in the case of combinatorial chemistry modifications, such as positional-scanning combinatorial libraries
(PSCL), where use of Cys is not desirable due to its propensity to form multiple disulfide bridges and also can oxidize easily by air.410,411 Analog OLA3 corresponds to the cyclic peptide containing the amide bond substituting the disulfide bridge between Cys6-Cys16 with Asp6-Dap16 (reverse orientation)388 (Figure 19 B), and analog OLA4 corresponds to the cyclic peptide containing the amide bond substituting the disulfide bridge with Dap6-Asp16 (direct orientation)388 (Figure 19 B).
Figure 19. OL cysteine-to-amino acid substitutions for disulfide bridge replacement amide bonds. A) In OLA3, Cys6 and Cys16 were replaced with Dap6 and Asp16, respectively. In OLA4, Cys6 and Cys16 were replaced with Asp6 and Dap16, respectively; B) the two possible cis-trans lactam configurations observed in disulfide bridge replacement.
3.4.1. Synthesis of native odorranalectin (OL)
We have developed an efficient Fmoc-solid phase approach for the synthesis of native
OL as shown in Scheme 3. Native OL was synthesized using a rink amide resin (0.66mmol/g loading). Peptide backbone was synthesized on a peptide synthesizer using standard Fmoc-
SPPS strategy412,413 and standard HBTU/HOBt/NMM synthetic protocol. Disulfide bridge formation between Cys6 and Cys16 was done on solid-support using iodine which simultaneously
60
removes the Trt protecting group and forms the disulfide bridge.414 After disulfide bond formation, final Boc deprotection and cleavage from the resin was carried out by a cleavage cocktail of
TFA:thioanisole:water (95:2.5:2.5 v/v/v), precipitated in cold ether, and purified by RP-HPLC.
Purity (≥95%) and mass was confirmed by MALDI-TOF and analytical RP-HPLC.
3.4.2. Synthesis of the linear analog (OL linear)
Linear analog (OL linear) was synthesized using a rink amide resin (0.66mmol/g loading) as shown in Scheme 3. Peptide backbone was synthesized on a peptide synthesizer using standard Fmoc-SPPS strategy412,413 and standard HBTU/HOBt/NMM synthetic protocol. Final Boc deprotection and cleavage from the resin was carried out by a cleavage cocktail of
TFA:thioanisole:water (95:2.5:2.5 v/v/v), precipitated in cold ether, and purified by RP-HPLC.
Purity (≥95%) and mass was confirmed by MALDI-TOF and analytical RP-HPLC.
Scheme 3. Fmoc-solid phase peptide synthesis of native OL and its linear analog. Reagents and conditions: a) Fmoc-AA-OH, standard Fmoc-SPPS deprotection and coupling protocols; b) I2 (10 eq), 2% anisole (v/v), NMP, r.t., 2x30 min; c) TFA:thioanisole:H2O=95:2.5:2.5 (v/v/v), r.t. 4 h.
61
3.4.3. Synthesis of amide analogs (OLA3 and OLA4)
The amide-to-disulfide bond substitution can be direct or reverse depending on the orientation of the carbonyl in the amide bond; thus, the two amide analogues for native OL were designed with Asp and Dap (Figure 19 B). Two different synthetic schemes had to be developed for efficient Fmoc-solid phase synthesis for Analogs OLA3 and OLA4, respectively (Scheme 5 and Scheme 6). An encountered problem when having Asp in a peptide sequence is aspartimide
(Asi) formation as a side-reaction. Succinimide ring closure is a well-documented side reaction in the synthesis of certain Asp-containing peptides.415,416 Asi formation during peptide synthesis can be either acid or base catalyzed (Scheme 4), with the kinetics of ring closure depending upon the nature and strength of the acid of base,417,418 the structure of the aspartate side-chain protecting group,419,420 and the aspartate carboxyl neighboring residue.417,421
In the case of analog OLA4, a modified synthesis was carried out in order to avoid Asi formation389,422-425 (Scheme 4). Indeed, previous studies have shown that, under basic or acidic conditions, aspartic acid derivatives with allyl, β-tert-butyl, benzyl and Dmab esters as side-chain protections may lead to undesired formation of Asi peptides.389,422-425 Moreover, the allyl side- chain-protecting group (Allyl) for aspartyl residues, while having its appeal in being orthogonal
(with respect to Fmoc/tert-butyl methodology), has been shown to be particularly prone to formation of Asi side reaction, where its occurrence also depends on the Asp-X sequence motif.415,420,426-429 When using the allyl ester carboxyl protecting group in Fmoc-SPPS, aspartimide side reaction does not occur during the allyl removal under palladium(0) treatment,427,430 but careful consideration must be taken during the Fmoc-Asp(OAllyl)-OH coupling and subsequent
Fmoc-deprotection steps to the peptide backbone. In the coupling reaction of Fmoc-Asp(OAllyl)-
OH, Asi formation will occur even in the absence of base if excess coupling reagent (DCC) is present,415 as will also occur during the base-induced Fmoc-deprotection step.417,418 Much effort has been made in trying to minimize this side reaction by using HOBt or 2,4-dinitrophenol as an additive to the Fmoc-deprotection solution,417 changing from piperidine to piperazine as the base in the Fmoc-deprotection,418 and using amide-backbone protection strategy.420,426
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Scheme 4. Aspartimide (Asi) side-product formation seen in Fmoc-Asp-OAllyl after standard Fmoc deprotection conditions.
Such a difference between the two synthetic approaches of the lactam analogs indicates that activation of the acid moiety of the side-chain when the aspartic acid is relatively close to the resin attachment point due to steric hindrance avoids aspartimide formation.389 This clearly demonstrates that cyclization of lactam analogs does not depend only on amino acid sequence but also on the orientation of the lactam bond.389
Analog OLA3 was synthesized using a rink amide resin (0.66mmol/g loading) (Scheme 5).
Peptide backbone was synthesized on a peptide synthesizer using standard Fmoc-SPPS strategy and standard HBTU/HOBt/NMM synthetic protocol. Selective deprotection of allyl group in Asp16
431-433 by treatment with Pd(Ph3P)4 and non-basic borane dimethylamine complex as scavenger, and selective Mtt removal431,434 in Dap6 was achieved with 2% TFA in DCM. The linear peptide was cyclized through an amide bond formation between Dap6 and Asp16 residues using PyBOP.
Final synthetic steps were performed as described above.
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Scheme 5. Fmoc-solid phase peptide synthesis of odorranalectin amide analog 3 (OLA3). Reagent and conditions: a) Fmoc-AA-OH, standard Fmoc-SPPS deprotection and coupling protocols; b) HN(CH3)2•BH3 (4 eq), Pd(PPh3)4 (0.1 eq), DCM, argon atmosphere, r.t., 2x30 min; c) TFA:thioanisole:DCM=2:3:95, r.t., 2x30 min; d) HOBt (2 eq), PyBOP (2 eq), DIEA (6 eq), DMF, r.t., 18h; e) TFA:thioanisole:H2O=95:2.5:2.5 (v/v/v), r.t. 4 h.
Analog OLA4 was synthesized using a rink amide resin (0.66mmol/g loading) (Scheme
6). Partial peptide backbone was synthesized on a synthesizer using standard Fmoc-SPPS strategy412,413 and standard HBTU/HOBt/NMM synthetic protocol, leaving Fmoc-Asp(OAllyl) as the last amino acid coupled. The linear partial peptide backbone was cyclized through an amide bond formation between Dap16 and Asp6 residues using PyBOP after selective deprotection of allyl group431-433 in Asp6 and selective Mtt removal431,434 in Dap16 as described above. After cyclization, remaining amino acids in the peptide backbone were coupled manually with a modified Fmoc deprotection422 protocol consisting of a mixture of piperidine:formic acid:NMP
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(20:5:75 v/v/v) and non-basic DIC/HOBt coupling conditions435 in DMF in order to overcome Asi formation (Scheme 4). Under applied experimental conditions no Asi was observed as indicated by analytical RP-HPLC (data hot shown). Once the remaining peptide backbone was built, final synthetic steps were performed as described above.
Scheme 6. Fmoc-solid phase peptide synthesis of odorranalectin amide analogue 4 (OLA4). Reagent conditions: a) Fmoc-AA-OH, standard Fmoc-SPPS deprotection and coupling protocols; b) HN(CH3)2•BH3 (4 eq), Pd(PPh3)4 (0.1 eq), DCM, argon atmosphere, r.t., 2x30 min; c) TFA:thioanisole:DCM=2:3:95, r.t., 2x30 min; d) HOBt (2 eq), PyBOP (2 eq), DIEA (6 eq), DMF, r.t., 18h; d) Fmoc-SPPS modified conditions for: Fmoc deprotection: piperidine:formic acid:NMP (20:%:75 v/v/v), r.t., 3x5 min; and manual coupling: Fmoc-AA-OH (4 eq), DIC (4eq), HOBt (4 eq), DMF, r.t., 90 min ; e) TFA:thioanisole:H2O=95:2.5:2.5 (v/v/v), r.t. 4 h.
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3.5. Conformational study
Circular dichroism (CD) is a convenient technique for studying the secondary structure of peptides in various media.436-442 Although the technique does not provide as detailed information as nuclear magnetic spectroscopy (NMR), it is one of the most widely used methods since conformational propensities of peptides under different conditions can be conveniently studied at low concentrations and therefore any potential aggregation problem can be avoided.
Trifluoroethanol (TFE), a solvent which has lower dielectric constant than water, has been useful in examining conformational preferences of peptides, since it has been shown to stabilize ordered secondary structures, such as β-turns.443-450 Since small cyclic peptides still have considerable mobility of their backbones, although are more conformationally restricted when compared to their linear counterparts,451-453 it is reasonable to expect that the disulfide bridge substitution with isosteric amides will also lead to significant conformational changes. Therefore, we would expect different CD spectra of the amide analogs OLA3 and OLA4 as well as the linear analog when compared to the native OL and linear OL in water and less polar TFE, due to their different conformational flexibility and the ability of TFE to promote intramolecular H-bonds and stabilize preferential conformation.443 In order to get a better insight into conformational changes induced by these amide-bond substitution analogs, we have also conducted molecular dynamics (MD) simulations.
3.5.1. Circular dichroism (CD) spectroscopy
The structural features of representative OL and its analogs, OLA3, OL4, as well as its linear analog were monitored by circular dichroism (CD) spectroscopy (Figure 20). The CD spectra were recorded in an aqueous medium and trifluoroethanol (TFE).443 Besides membrane- mimicking properties, TFE is also known to induce formation of the stable conformations in peptides which are otherwise unstructured in aqueous solutions.436,443 In order to increase solubility of peptides in aqueous media and to inhibit potential peptide aggregation at the concentrations required for CD experiments, the analyzed peptides were dissolved in 0.5% aqueous AcOH.454
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The interpretation of these CD spectra is rather difficult, due to the fact that none of the spectra can be attributed to a single conformation. The CD spectra of the native OL (Figure 20 A) in 0.5% AcOH exhibits a minimum at approximately 190 nm and a sharp maximum around 230 nm, characteristic of the disulfide bridge, in agreement with the characteristic turn structure.380
Water replacement with less polar 100% TFE had no effect on the CD spectra of the native OL peptide, suggesting a restricted and locked peptide turn-type conformation, due to the presence of the disulfide bridge. As expected, due to lack of structural constraint, linear OL peptide (Figure
20 B) shows characteristic random coil spectra with a weak minimum at 195 nm, whereas in TFE the weak minimum shifted to 185 nm.
Figure 20. Circular dichroism (CD) spectra of native OL and its analogs in 0.5% AcOH and 100% TFE. A) Native OL, B) OL linear, C) OLA3, and D) OLA4.
The CD spectra of OL amide analog OLA3 (Figure 20 C) and OLA4 (Figure 20 D) are similar in aqueous solution, but markedly different from the native OL spectra in TFE solutions,
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indicating a less restricted peptide conformation than native OL, due to significant differences in structural flexibility and conformations induced by the disulfide-to-amide substitution.455 This change can be attributed to the loss of conformational constraint due to the disulfide bond replacement.455,456 The CD spectrum of OLA3 and OLA4 in 0.5% AcOH are characterized by the minimum at 190 nm and a weak maxima around 230 nm, whereas in 100% TFE, the CD minimum at 190 nm is inverted to a sharp maxima at the same wavelength, and the weak maxima at 230 nm is completely lost and the intensity of the maximum is decreased slightly and shifted towards shorter wavelengths.
When we compare the CD spectra of the native OL (Figure 20 A) with those of its analogs OLA3 (Figure 20 C) and OLA4 (Figure 20 D), the differences in TFE solution are again remarkable, showing clearly that replacing the disulfide bond by an amide bond has a big impact on the conformation of the peptide.
3.5.2. Molecular dynamics (MD) simulations
MD calculations were performed to further explore the conformational differences caused by the disulfide bridge replacement by amide bonds in both orientations. A conformational analysis using conformational sampling and backbone superimposing and clustering using the native OL sequence as well as its amide analogs. In addition, to analyze the conformational effects of the amide orientation, a pairwise RMSD distance matrix was computed for both amide analogs, respectively.
Interestingly, as shown in Figure 21, MD studies show clear differences in conformation based on the orientation of the amide bond for the native OL amide analogs. The best overlay of native OL and its amide analogs is seen with OLA4 (Figure 21 B), which exhibited the lowest
RMSD of 2.59 Å with a percent population of 80%.
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Figure 21. Backbone overlays of native OL peptide with its amide analogs. Native OL (purple) with A) OLA3, and B) OLA4. The RMSDs are shown underneath each overlay.
3.6. Thermodynamic assessment study
3.6.1. Assessment of binding interaction of native OL and its amide analogs with fucosylated- glycoproteins
To study the binding profiles of native OL and its amide analogs, fetuin and asialofetuin
(ASF) were chosen as the glycan binding partner, since they are considered two models of fucose-containing glycoproteins. The main difference between these two glycoproteins is the presence (sialylation) and absence (desialylation) of terminal sialic acid on the glycan surface, respectively. The binding affinities of the native OL for fetuin (Figure 22 B) and ASF (Figure 22 A) were assessed by isothermal titration calorimetry (ITC) and show different binding profile. The measured Kd for native OL and fetuin (Kd = 520 μM; Figure 22 B) is significantly lower (by one order of magnitude) than ASF (Kd = 63 μM; Figure 22 A). This might suggest that the difference in affinity might be due to accessibility of OL to bind to a non-sialylated fucose vs. heavily sialylated fucose glycoproteins.
As for the amide analogs OLA3 and OLA4, ITC binding data for the fucosylated- glycoproteins, fetuin and asialofetuin, show markedly different binding profiles as well.
Surprisingly, replacement of the native OL disulfide bridge seen in OLA3 (Figure 22 B and D) results in complete loss of binding affinity to fetuin and ASF, while the disulfide bridge replacement with the specific amide orientation seen in OLA4 (Figure 22 E and F) results in comparable binding affinity to the fucosylated glycoproteins. No binding was observed for OLA3
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with both models of fucosylated glycoproteins (Figure 22 C and D). Interestingly, the measured Kd for OLA4 and fetuin (Kd = 227 μM; Figure 22 F), is slightly higher than the native OL peptide
(Figure 22 B), as well as comparable binding to ASF (Kd = 85 μM; Figure 22 E). It is worth mentioning that binding studies were also conducted with the OL linear analog, and no binding was observed for either glycoprotein (data not shown).
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Figure 22. Isothermal titration calorimetry (ITC) data of native OL and its amide analogs with fucosylated glycoproteins. Native OL (3 mM) with A) ASF (250 μM), and B) fetuin (250 μM). OLA3 (3mM) with C) ASF (250 μM), and D) fetuin (250 μM. The top panel shows the experimental ITC data and bottom panel shows a fit to one-site model of the binding data using MicroCal analysis software (Origin 7.0). The best values for the stoichiometry (n), binding affinity (Ka), dissociation constant (Kd), enthalpy (ΔH), and change in entropy with respect to temperature (-TΔS) are shown in the graph below.
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Figure 22. Isothermal titration calorimetry (ITC) data of native OL and its amide analogs with fucosylated glycoproteins. OLA4 (3 mM) with E) ASF (250 μM), and F) fetuin (250 μM). The top panel shows the experimental ITC data and bottom panel shows a fit to one-site model of the binding data using MicroCal analysis software (Origin 7.0). The best values for the stoichiometry (n), binding affinity (Ka), dissociation constant (Kd), enthalpy (ΔH), and change in entropy with respect to temperature (-TΔS) are shown in the graph below.
In the present study, the amide analogs showed a difference in binding profiles compared to the parent disulfide bond peptide. An obvious interpretation is that the lactam cyclization does not constrain the turn in a conformation similar to that imposed by the disulfide bond present in the native peptide.389 The ITC binding experimental data is in qualitative agreement with the MD studies indicating that one hypothesis to explain the complete loss of binding affinity seen in
OLA3 to fucosylated glycoproteins would be that the disulfide bridge is involved directly in L- fucose binding and that, as a consequence, its replacement by the lactam bond in the particular reverse orientation disrupts the H-bonding pattern necessary for the fucose binding site and therefore compromising the conformation necessary for binding activity. Furthermore, the ITC comparable experimental data for native OL and OLA4 (albeit weaker) (Figure 22 A-B to E-F) further supports the MD studies showing that the direct orientation seen in this particular peptide analog seems to portray the necessary peptide backbone conformation for fucose-binding activity when replacing the disulfide bridge.
3.7. In vitro cell study
3.7.1. Assessment of binding interaction of native OL and its amide analogs by in vitro lectin- binding cell-based assay
Since our the ITC binding studies with native OL suggest that the difference in affinity between ASF and fetuin might be due to accessibility of OL to bind to non-sialylated fucose vs. heavily sialylated fucose containing glycans, we conducted in vitro cell staining studies to assess the binding behavior of native OL and its analogues to cell-surface expressed fucosylated glycoproteins, as well as further explore the disulfide bridge replacement by the two amice bond orientations. A total of six cell lines were chosen to examine the fucose-binding effect of native
OL and its amide analogs, OLA3 and OLA4. The cell lines chosen as the normal (control) were
BJ (ATCC® CRL-252TM), human normal foreskin fibroblast cell line. The remaining cell lines were all human cancer cell lines, which are known to express cancer-specific glyco-epitopes on their surface.457-459 The cancer cell lines studied are: T-47D (ATCC® HTB-133TM), human breast epithelial ductal carcinoma; MCF-7 (ATCC® HTB-22TM), human breast epithelial adenocarcinoma;
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MDA-MB-231 (ATCC® HTB-26TM), human breast epithelial adenocarcinoma; Hep G2 (ATCC®
HB-8065TM), human liver epithelial hepatocellular carcinoma; and PSN-1, human pancreatic adenocarcinoma. All cell lines were grown in their respective media, plated in 96-well plates, incubated overnight at 37°C in a CO2 atmosphere incubator, and fixed with 4% paraformaldehyde. Fixed cells were also treated with 3% BSA in PBS buffer, prior to any fluorescently-labeling studies. The T-47D breast cancer cell line460 is representative for breast cancer cells in several aspects: (i) by exhibiting aberrant expression of core glycosyltransferases, and (ii) by expressing mainly core-type sialyloligosaccharides typical for several established breast cancer cell lines461 and ductal carcinomas of the breast.462,463
Control fixed cells staining studies with known FITC-labeled lectins (Vector Labs) were done with BJ, T-47D, and MCF-7 cell lines to determine carbohydrate expression on the cell- surface (Figure 24). For terminal sialic acid, Sambucus nigra (SNA-FITC) (Figure 24 A, B, I, J, Q, and R) was used, since this lectin is specific for sialic acid attached to terminal galactose in
α(2,6)- and to a lesser degree, α(2,3)- linkage. For L-fucose detection, two FITC-labeled lectins were used: Ulex europaeus agglutinin I (UEAI-FITC) (Figure 24 C, D, K, L, S, and T), which binds to glycoproteins and glycolipids containing α(1,2)- linked fucose (terminal fucosylation); and
Aleuria aurantia (AAL-FITC) (Figure 24 E, F, M, N, U, and V), which prefers to fucose linked
α(1,6)- to N-acetylglucosamine (GlcNAc) or to fucose linked α(1,3)- to N-acetyllactosamine
(LacNAc) related structures (core fucosylation).
In order to conduct the same labeling studies with fixed cell lines, native OL and its two amide analogues (OLA3 and OLA4) were fluorescently labeled (Figure 23). Synthesis was carried out as described previously for all three peptides, with the addition of a PEG(20) linker
(Novabiochem) at the N-terminus, followed by fluorescein (FAM) coupling, to allow sufficient distance from the peptide and FAM moiety to avoid possible interference in the binding site. The cell-labeling capability of native OL peptide was examined (OL-FAM) (Figure 24 G, H, O, P, W, and X). In addition, cells were also treated with sialidase (neuraminidase) to remove terminal sialic acid on the cell surface prior to treatment of FITC-labeled lectins (Figure 24 B, D, F, H, J, L,
N, P, R, T, V, and X).
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Figure 23. Structures of OL analogs used in the in vitro cell-based studies.
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Figure 24. Cell-based lectin studies with fluorescently labelled lectins. A-H) Fixed BJ (10,000 cells/well); I-P) T-47D (30,000 cells/well); and Q- X) MCF-7 cell lines (30,000 cells/well). Pictures A, C ,E, G, I, K, M, O, Q show cells non-treated (controls), and pictures B, D, F, H, J, L, N, P, R show cells treated with 50mU sialidase. Cells were all stained with known FITC-labeled lectins accordingly (40 μg/mL), and OL-FAM (60 μg/mL).
Figure 25. Fluorescence readout for each cell line with their corresponding fluorescently-labeled lectins (SNA-FITC, UEA1-FITC, and AAL-FITC). A) BJ, B) T-47D, C) MCF-7, and D) OL-FAM labeling of cell lines.
Control cell-surface labeling of the BJ, T-47D, and MCF-7 cells lines with FITC-labeled lectins show that terminal sialic acid is heavily expressed in T-47D cell line (Figure 24 I), while MCF-7 cell line expresses more of α(1,3)- and α(1,6)- fucosylated structures (Figure 24 U). In addition, the BJ cell lines shows no significant binding of the known FITC-labeled lectins (Figure 24 A-F), rendering then a good control cell line for further experiments. Treatment of the cells with sialidase only had a drastic effect in the T47-D and slightly significant in the MCF-7cell lines in the binding of SNA-FITC, when comparing the control (Figure 24 I and Q) to the treated cells (Figure
24 J and R). Surprisingly, sialidase (neuraminidase) treatment did not have any effect in the binding of the fucose-specific FITC-labeled lectins on any cell line (Figure 24 D, F, L, N, T, and
V)). In addition, pictures taken are in agreement with the fluorescence measurements (Figure 25), which indicates that the BJ cell line had minimal detection of fucosylated glycans on their cell-
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surface, and small presence of terminal sialic acid (Figure 25 A). The T47-D cell line has the highest terminal sialic acid expression on the cell-surface, followed by α(1,6)- and α(1,2)- fucosylated glycans (Figure 25 B), and the MCF-7 cell line shows high expression on both terminal sialic acid and high levels of α(1,6)- fucosylated glycans on their cell-surface (Figure 25
C). No background fluorescence was detected in the assay (Figure 25).
Preliminary staining studies with 4% paraformaldehyde fixed cells and OL-FAM shows that native OL labels preferentially MCF-7 cell line (Figure 24 W) displaying higher expression of terminal and core fucosylated cell-surface antigens over the T-47D (Figure 24 O) breast epithelial ductal carcinoma cell line,378,464 while shows no binding to the BJ fibroblasts (Figure 24 G). In addition, native OL shows similar cell-labeling profile as AAL-FITC with BJ (Figure 24 E-F to G-
H), T-47D (Figure 24 M-N to O-P), and MCF-7 (Figure 24 U-V to W-X) cell lines. Moreover, treatment of the cells with sialidase did not have any effect on binding of the OL-FAM labeling
(Figure 24 H, P, and X) when compared to their respective controls, as was the case for all fucose-specific FITC-labeled lectins. This suggests that sialic acid removal from the cell-surface in a fixed cell assay is not significant enough to detect a change in fucose-binding, as was the case seen in the ITC binding of native OL and the glycoproteins, ASF (Figure 22 A) and fetuin
(Figure 22 B). In addition, pictures taken are in agreement with the fluorescence measurements, indicating that OL-FAM binds selectively to both MCF-7 and T-47D cell lines (Figure 24 O and W,
Figure 25 D), with a higher preference for the former cell line, having higher expression of both terminal- and core-fucosylated cell-surface glycans. Most importantly, OL-FAM shows no binding to the normal BJ cell line (Figure 24 G and Figure 25 D), rendering a possibility for further development as a lead structure for selective drug-delivery and/or therapeutics.
Continuation of the staining studies with OL-FAM, OLA3-FAM and OLA4-FAM was carried out on additional cancer cell lines (HEP-G2, PSN-1, and MDA-MB-231), in addition to the three main cell lines studied so far (BJ, T47-D and MCF-7) to assess binding preference, as well as any change in the binding of the amide analogs regarding the disulfide-to-amide bond replacement (Figure 26). OL-FAM labeled all cancer cell lines (Figure 26 F, J, N, R, and V) preferentially over the BJ fibroblasts (Figure 26 B), in the following decreasing order: MCF-7 =
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MDA-MB-231 > PNS-1 > HEP-G2 > T47-D) (Figure 26 and 27). As expected, OLA3-FAM showed no significant labeling of any cell line in pictures and fluorescence measurements (Figure 26 C,
G, K, O, S, W and Figure 27), even at higher labeling concentration (120 μg/mL), and no signs of aggregation were even detected. Interestingly, OLA4-FAM showed significant binding to all cancer cell lines (Figure 26 H, L, P, T and X and Figure 27), albeit to a lower degree when compared to OL-FAM (Figure 26 F, J, N, R, V and Figure 27), both in the same concentration (60
μg/mL). It is worth mentioning that the decrease in fluorescence might be due to slight aggregation observed during the experiment with OLA4-FAM. In addition, the weaker cell-labeling observed for OLA4 (Figure 26 H, L, P, T, X and Figure 27) in comparison to OL (Figure 26 F, J,
N, R, V and Figure 27) could indicate an overall weaker binding to fucosylated-carbohydrate antigens on the cell-surface of the cells. Moreover, these cell-labeling results complement the ITC binding assessment studies (see section 3.6.1.), where a similar binding affinity is seen between
OL and OLA4 and fetuin/asialofetuin (Figure 22 A-B to E-F), whereas no binding was observed for OLA3 (Figure 22 C and D). Of important note, a great difference in cell-labeling is seen when comparing the AAL-FITC lectin (Figure 26 Q and U) to OL-FAM (Figure 26 R and V) to the PSN-1 and MDA-MB-231 cell lines. This may suggest that the OL peptide could have preference for other fucose-type linkages, in addition to those preferred by AAL-FITC.346
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Figure 26. Cell-based lectin studies with fluorescently labelled peptides. Fixed BJ (10,000 cells/well), T-47D, MCF-7, Hep G2, PSN-1 and MDA-MB-231 cell lines (30,000 cells/well). Pictures show cells stained with OL-FAM (60 μg/mL), OLA3-FAM (120 μg/mL), and OLA4-FAM (60 μg/mL).
Figure 27. Cell-based lectin studies with fluorescently labelled peptides. Fluorescence readout for each cell line with their corresponding fluorescently-labeled peptides.
3.7.2. Assessment of binding interaction of native OL by in vitro competitive inhibition cell-based assay
To further explore the binding selectivity of native OL towards cancer cells vs. normal cells, we conducted in vitro cell staining studies to assess the binding behavior of native OL to cell-surface expressed fucosylated glycoproteins The cell lines chosen were BJ (ATCC® CRL-
252TM), human normal foreskin fibroblast was chosen as the normal (control) cell line, and the
MCF-7 (ATCC® HTB-22TM), human breast epithelial adenocarcinoma, as a model cell line for containing high expression of fucosylated-glycans. The IC50 values of OL and the MCF-7 and BJ cell lines were evaluated using a competitive binding assay. This assay mode is usually preferred because the high avidity of the expressed cell-surface glycans usually leads to the underestimation of the Kd values in most inhibition assays. In the competitive binding mode, increasing the concentration of the unlabeled ligand is used to displace the fluorescently-labeled compound, leading to disruption of the association between the binding partners, therefore, a decrease in fluorescence signal. The IC50 value can be calculated from the range of increasing concentrations of the unlabeled ligand used in a competitive binding assay mode. Because the
IC50 for a given compound varies depending on the assay conditions and the compound’s mechanism of inhibition, the accurate initial estimation of the Kd values of drug candidates
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identified from screening assays is often desired. Several models based in principle on the
465-469 original Cheng–Prusoff analysis have been used to convert IC50 to Kd values. Alternatively, in the current study, Kd values for the selected model fucosylated-glycans (ASF and fetuin) with low and high micromolar affinity for OL were measured experimentally by ITC (Figure 22 A and
B), and those values were compared with the corresponding IC50 value towards the MCF-7 cell line, which expresses high levels of fucosylated-glycans. We evaluated native OL to compete with
OL-FAM for fixed MCF-7 and BJ cell-surface glycans (Figure 28 A and B). Non-labeled native OL was used as a noncompeting inhibitor of the OL-FAM/MCF-7 cell surface interaction. The non- labeled OL was titrated in a concentration range from 0.1 μM to 1 mM All cell lines were grown in their respective media, plated in 96-well plates, incubated overnight at 37°C in a CO2 atmosphere incubator, and fixed with 4% paraformaldehyde. Fixed cells were also treated with 3% BSA in
PBS buffer, prior to any competitive assay studies.
Figure 28. Competitive binding assay of OL with cancer and normal cell lines. MCF-7 cell (30,000 cells/well) and BJ cells (10,000 cells/well). Native OL (0.1 μM to 1 mM) inhibition of OL-FAM (60 μg/mL) binding to fixed cells. Curve, Fluorescence signal (RFU) versus log [non-labeled, M], were plotted as mean of 3 replicate measurements. The IC50 value was obtained by non-linear regression analysis using the Graph Pad Prism 5.04.
Competitive assay clearly shows that native OL inhibited the MCF-7/OL-FAM interaction with an IC50 value of 1.94 μM (Figure 28 A). In addition, results from competitive assay with the
BJ cell line show no binding (even non-specific (Figure 28 B), further confirming OL’s selectivity for the cancer cell lines.
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3.8. Cytotoxicity study
3.8.1. Toxicity towards human normal and cancer cell lines
To further assess the therapeutic potential of native OL and its amide analogs, we tested the in vitro cell viability of native OL as well as its amide analogs OLA3 and OLA4 peptides was determined after 72 h exposure, and assessed using Cell Titer-Glo Luminescent Cell Viability
Assay (Promega), a homogeneous method of determining the number of viable cells in culture based on quantitation of the ATP present using the Cell Titer Glo colorimetric assay. The cell line chosen was BJ (ATCC® CRL-252TM), human normal foreskin fibroblast as the normal (control) cell line. A known cytotoxic drug Adriamycin (Doxorubicin)470 and 20% DMSO471-473 were used as positive controls for monitoring cell viability.
Figure 29. Cell viability assay shown as percentage (%) viability with BJ cell line (10,000 cells/well) and OL, OLA3, and OLA4 at different concentrations. Positive controls are shown (doxorubicin 10 μM, and 20% DMSO).
As seen in Figure 29, native OL and its analogs show no toxicity in cell viability assays after 72 h, even at the highest tested concentration of 2 mg/mL. Doxorubicin and 20% DMSO were used as positive controls. It is important to mention that in this assay, up to 5% v/v final concentration of DMSO was added to increase tested peptides’ solubility. Therefore, potential
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aggregation due to lower solubility of the peptides at higher concentrations may contribute to any observed slight decrease in cell viability.451,452 Although DMSO is hemolytic,472,473 our control experiments showed that under the applied experimental conditions did not cause appreciable toxicity. In addition, this experimental data shows the advantages of amide analogs in comparison to the native OL for the development of novel drug delivery systems (i.e. lower toxicity).
3.9. Discussion and conclusions
Although many scientific problems and technical developments need to be solved, lectin- mediated drug delivery is more than just an interesting idea. The most promising drug candidates from the lectin families in preclinical and clinical evaluation are: Cimetidine (Tagamet;
GlaxoSmithKline), a histamine receptor that belongs to the selectin family; dendritic cell-specific
ICAM3-grabbing non-integrin 1 (DC-SIGN, also known as CD209) from the C-type lectin family; myelin-associated glycoprotein (MAG, also known as sialic acid-binding immunoglobulin-like lectin 4A (Siglec 4A)), as an example of an I-type lectin; and PA-I galactophilic lectin (PA-IL), fucose-binding lectin PA-ILL and minor component of type 1 fimbriae (FimH) as representatives of bacterial lectins; and neuraminidase inhibitors Zanamivir (Relenza: GlaxoSmithKline),
Oseltamivir phosphate (Tamiflu; Genentech).474 Most lectins are large and unlikely to be used as drug carriers because of their immunogenicity and toxicity.475 Smallest peptides or even organic molecules which can mimic the function of lectins are ideal candidates for this purpose.475 As the smallest lectin, odorranalectin (OL) has the potential for drug delivery and targeting because of its several unique characteristics. Its selectivity for L-fucose and very low immunogenicity make OL an excellent candidate for drug delivery to targeted sites, such as tumor-associated fucosylated antigens implicated in the pathogenesis of several cancers,163,339,340,317-319,326 for overcoming the nonspecificity of most anticancer agents.
With this in mind, we synthesized four OL analogs and investigated the effects of structural modification on the disulfide bridge by amide replacement in both direct and reverse orientations. In addition, there is substantial evidence in the literature showing that substitution of the disulfide bridge with an amide bond may afford derivatives with comparable or improved
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activities.375,376 We have devised a simple and robust preparation strategy whereby all analogs were synthesized on a solid support using Fmoc methodology, and their syntheses were straightforward (Scheme 3 and 5), with the exception of the solid-phase synthesis of OLA4
(Scheme 6), which turned out to be particularly challenging due to undesired aspartimide side- product formation (Scheme 4).389,422-425 Our strategy for the solid-phase synthesis of OLA4 involved rearranging the order of the linear cyclization step before final backbone assembly of the peptide with the use of coupling procedure in the absence of basic conditions,435 as well as an acidic modification of the Fmoc-deprotection step422 (Scheme 6). Crucial steps in the synthesis of all peptides analogs for this study were monitored using RP-HPLC and MALDI-TOF MS. The desired native OL and its analogs were obtained in satisfactory yields.
Several studies have pointed out the impact of disulfide bridge replacement by amide bonds on cyclic peptides’ conformation and biological activity.367,369,370,367-369,371-374 In general, replacing the disulfide bridge with both possible orientations of the amide bond (direct or reverse) results in removal of the locked S-S bond, affecting therefore the peptide conformation.396 The effect of the substitution of the disulfide bridge in the conformation of native OL was assessed by
CD spectroscopy comparison with its analogs (Figure 20). Although the conformations of the peptides cannot be attributed to a single structure, rather a combination of structures, there are both similarities and well as drastic differences between the CD spectra of native OL and its analogs in TFE solution. The most striking feature when comparing CD spectra is that the native
OL peptide does seem to have less degree of conformational flexibility as its amide analogs,
OLA3 and OLA4. MD simulations were also performed to further explore the conformational differences caused by substituting the disulfide bridge with both possible orientations of the amide bond (direct and reverse) (Figure 21) and show that OLA4 can adopt a similar conformation to native OL. Our experimental CD data fully supports the MD simulations indicating higher conformational flexibility of the amide analogs. In addition, MD calculations showed excellent backbone overlay of native OL with only one of the two possible amide orientation substitution analogs, OLA4.
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Besides conformational changes, disulfide bridge replacement by both orientations of the amide bond altered the biochemical properties of native OL. Of notable impact is the binding ability of these peptides to L-fucose. ITC data further confirms the conformational studies, where only one of the amide analogs in the particular direct orientation (OLA4) possesses comparable binding affinity for L-fucose as native OL (Figure 22). Based on the role of the disulfide bridge on the L-fucose binding site of native OL and our experimental data showing that OLA3 (with the amide bond in reverse orientation) has no binding towards L-fucose, we can assume that the conformation held by the disulfide bridge and its amide bond replacement in direct orientation are indispensable for the activity of the peptides.
To further elucidate the potential of native OL and its amide analogs to bind to cell- surface fucosylated glycan, we conducted in vitro lectin-cell staining studies with both cancer- derived and normal human epithelial cell lines. Our studies reveal preferential binding of native
OL towards cancer cell lines rather when compared to healthy cells (Figures 26, 27 and 28).
Native OL has preference in binding to fucosylated cell-surface glycans on human breast primary
MCF-7, and metastatic MDA-MB-231476 cancer cells, as well as the pancreatic PSN-1 and liver
Hep-G2 cell lines, while showing no binding to the BJ fibroblasts. Therefore, we hypothesize that
374,376-378 OL can aid in targeted drug delivery to cancer cells overexpressing α-L-fucose, an essential component of malignant and metastatic phenotype of many human cancers.376,377,379,477
In addition, the particular amide modification of the disulfide bond in the direct orientation (OLA4) results in comparable peptide binding properties, which opens up the possibility to modify OL via a combinatorial approach to explore further peptide modifications. The assessment of native OL and its analogs cytotoxicity is an important secondary screen assay, mainly because this assay eliminates cytotoxic analogs. Our experimental data shows no significant toxicity of the peptides used in this study, even at very high mM concentrations (Figure 29).
In conclusion, binding studies of native OL and its analogs reported in this work reveal some of the key structural requirements for L-fucose binding capability on the complex oligosaccharide substrates as well as on the cell-surface glycosylated antigens. Both the disulfide bridge and a direct amide bond orientation are indispensable for the peptide to adopt the H-
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binding pattern needed for appropriate backbone conformation flexibility necessary for fucose binding activity. In addition, amide analogs are synthetically more accessible than the parent peptide since elimination of cysteine further avoids unwanted cysteine oxidations or multiple disulfide bridges formed during peptide synthesis,410,411 allowing for further structural optimization using a combinatorial chemistry approach. Overall, the research described in this study demonstrates that new ‘lectin-mimicking’ peptides derived from OL natural product have the potential to be further developed as anticancer drugs, and as vectors for the targeted delivery of imaging and/or therapeutic agents.
3.10. Materials and methods
3.10.1. Chemicals and instrumentation
Rink Amide MBHA resin was obtained from Novabiochem (Gibbstown, NJ, USA). Fmoc- protected amino acids, (5,6)-FAM and coupling reagents (HOBt, HBTU, PyBOP) were purchased from Chem-Impex (Wood Dale, IL) or Novabiochem. DIC was purchased from Acros Organics
(Thermo Fisher Scientific, Waltham, MA). Kaiser test was purchased from AnaSpec (Fremont,
CA). All solvents were purchased from Fisher Scientific (Atlanta, GA) or Sigma–Aldrich, and were high-performance liquid chromatography (HPLC) grade. Fetuin, ASF, BME and iodine were purchased from Sigma-Aldrich (St. Louis, MO).
Linear peptidyl-resin precursors were synthesized on a PS3 automated peptide synthesizer
(Protein Technologies Inc., Tucson, AZ). Mass spectrometry was performed on MALDI-TOF
Vogager-DE™ STR (Applied Biosystems, Foster City, CA) in reflector-mode using α-cyano-4- hydroxycinnamic acid as a matrix and in positive mode. Analytical RP-HPLC analyses and peptide purifications were performed on 1260 Infinity (Agilent Technologies, Santa Clara, CA) liquid chromatography systems equipped with a UV/Vis detector. For analytical RP-HPLC
-1 analysis, a C18 monomeric column (Grace Vydac, 250 x 4.6 mm, 5 µm, 120 Å), 1 mL.min flow rate, and elution method with a linear gradient of 2→100% B over 45 minutes, where A is 0.1%
TFA in H2O, and B is 0.08% TFA in CH3CN was used. For peptide purification, a preparative C18 monomeric column (Grace Vydac, 250 x 22 mm, 10 mm, 120 Å) was used. Elution method was
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identical to the analytical method except for the flow rate, which was 20 mL.min-1. CD spectra were recorded on a JASCO 810 spectropolarimeter (Easton, MD) using a quartz cell of 0.1 mm optical path length. Spectra were measured over a wavelength range of 180–250 nm with an instrument scanning speed 200 nm.min-1 and a response time of 1 s. The concentrations of peptides were 0.1–0.2 mM.
Cell counting was analyzed by a cell counter (Nexelom BioSciences, Lawrence, MA). Cell culture were grown in a HeraCell 2401 incubator (Thermo Fischer, Waltham, MA). Cell viability and fluorescence assays were analyzed on a Synergy H4 microplate reader (BioTek, Winooski,
VT). Cell-based fluorescent pictures were taken with a fluorescent microscope (Olympus,
Waltham, MA) and camera (Photometrics, Tucson, AZ). iTC200 was purchased from MicroCal,
LLC (Worcestershire, UK).
3.10.2. Human cell lines and reagents
Human cell lines were purchased from American Type Culture Collection (ATCC,
Manassas, VA). Control antibiotics and enzymes were purchased from Sigma-Aldrich (St. Louis,
MO). Cell culture media and PBS buffers were purchased from Fisher Scientific (Pittsburg, PA).
FITC-labeled lectins were purchased from Vector Labs (Burlingame, CA). Cell Titer-Glo
Luminescent Cell Viability Assay was purchased from Promega (Madison, WI).
3.10.3. General procedure for peptide synthesis and purification
All linear peptidyl-resin precursors for native OL and analogs were synthesized by Fmoc-
SPPS on Rink amide MBHA resin (substitution 0.66 mmol/g, 0.25 mmol scale) using automated peptide synthesizer when indicated (see section 3.4). Amino-acid couplings were done by using double couplings with six-fold excess of amino acids and coupling reagents (HOBt/HBTU) in 0.4M
NMM in DMF. Fmoc-deprotection cycles were carried out using 20% piperidine in DMF solution.
Linear peptidyl native OL peptide was synthesized on an automated peptide synthesizer. Fmoc was used for Nα-protection with the exception of the last amino-acid incorporated, Boc-Tyr(tBu)-
OH, and the following groups were chosen for protecting side-chain functionalities: Boc for Lys;
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tBu for Thr, Ser, and Tyr; Pbf for Arg; Trt for Asn and Cys. After assembly of the complete linear peptide sequence, solid-phase cyclization was achieved by disulfide bridge formation with subsequent removal of Trt group and final cyclization with iodine (10 eq) and 2% anisole in NMP
(2x30 min).414
For amide analog OLA3, linear peptidyl OLA3 peptide was synthesized on an automated peptide synthesizer. Fmoc was used for Nα-protection with the exception of the last amino-acid incorporated, Boc-Tyr(tBu)-OH, and the following groups were chosen for protecting side-chain functionalities: Boc for Lys; tBu for Thr, Ser, and Tyr; OAllyl for Asp; Pbf for Arg; Trt for Asn; and
Mtt for Dap. After assembly of the complete linear peptide sequence, the Nα-Boc protected resin was subjected to Pd(0) treatment with Me2N•BH3 (6 eq), Pd(PPh3)4 (0.1 eq) in DCM under argon atmosphere for 30 min,478 and the procedure was repeated twice, followed by washings with
0.2%TFA in DCM (3 x 1 minute), DCM (5 x 1 minute), and 5% DIEA in DCM (3 x 1 min).
Following allyl removal, the Mtt protecting group was removed by stirring a solution of
TFA:thioanisole:DCM (2:1:97 v/v/v) for 30 min,430 followed by extensive washings of the resin with
DCM. Once the side-chains of Dap and Asp were exposed, linear cyclization was carried out overnight by using PyBOP/HOBt/DIEA (2 eq each), followed by subsequent washings with DMF and DCM.
In the case of analog OLA4, linear peptidyl OLA4 peptide was synthesized on an automated peptide synthesizer. Fmoc was used for Nα-protection with the exception of the last amino-acid incorporated, Boc-Tyr(tBu)-OH, and the following groups were chosen for protecting side-chain functionalities: Boc for Lys; tBu for Thr, Ser, and Tyr; OAllyl for Asp; Pbf for Arg; Trt for
Asn; and Mtt for Dap. After assembly of the partial linear peptide sequence, Fmoc-Asp(OAllyl)-
OH was incorporated using six-fold amino-acid and DIC/HOBt in NMP for 1.5 h, then the Fmoc- protected resin was subjected to Pd(0) treatment with Me2N•BH3 (6 eq), Pd(PPh3)4 (0.1 eq) in
DCM under argon atmosphere for 30 min,478 and the procedure was repeated twice, followed by washings with 0.2%TFA in DCM (3 x 1 min), DCM (5 x 1 minute), and 5% DIEA in DCM (3 x 1 min). Following allyl removal, the Mtt protecting group was removed by stirring a solution of
TFA:thioanisole:DCM (2:1:97 v/v/v) for 30 min,430 followed by extensive washings of the resin with
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DCM. Once the side-chains of Dap and Asp were exposed, linear cyclization was carried out overnight by using PyBOP/HOBt/DIEA (2 eq each), followed by subsequent washings with DMF and DCM. Following linear cyclization, the rest of the linear peptide backbone was assembled using a six-fold of the Fmoc-amino acid and DIC/HOBt in DMF for coupling, and Fmoc- deprotection was done using 20% piperidine, 5% formic acid in DMF (3 x 5 min).479 Fmoc was used for Nα-protection with the exception of the last amino-acid incorporated, Boc-Tyr(tBu)-OH, and the following groups were chosen for protecting side-chain functionalities: Boc for Lys; tBu for
Ser and Tyr.
Fluorescently-labeled OL-FAM, OLA3-FAM and OLA4-FAM were synthesized using standard Fmoc-SPPS methodology as reported previously, except that the last amino acid, Boc-
Tyr(tBu)-OH, was replaced by its Fmoc-analog, Fmoc-Tyr(tBu)-OH, in order to add the fluorescein moiety. After cyclization, Fmoc deprotection was done with 20% piperidine and a linker, Fmoc-PEG(20)-OH, was coupled using standard Fmoc-SPPS methodology, followed by subsequent Fmoc deprotection and coupling of fluorescein (5,6-FAM) overnight using DIC/HOBt
(10 eq of both 5,6-FAM and coupling reagents) in DMF.480,481
3.10.4. Circular dichroism (CD) spectroscopy
All CD spectra were recorded on JASCO 810 spectropolarimeter at 25°C using a 0.1 cm path length cell. The spectra were acquired in the range 180–250 nm, 1 nm bandwidth, four accumulations and 200 nm.min-1 scanning speed. All spectra were obtained using 0.1–0.2 mm concentrations in 0.5% AcOH, 0–100% TFE/water (v/v) solution. Each experiment was repeated at least once and at various concentrations. No concentration-dependent CD spectral changes were observed.
3.10.5. Molecular dynamics (MD) simulations
The MD simulations were performed by Dr. Franco Medina’s group at Torrey Pines
Institute for Molecular Studies, Port St. Lucie, FL.
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Conformational analysis was performed using the natural ligand and its linkage analogues. A file containing 20 NMR solution structures of natural OL (pdbid: 2JQW) was downloaded from the
Research Collaboratory for Structural Bioinformatics web service. One of the models was selected as the starting point for OL. Maestro v9.3 was used to build the analogues by replacing the disulfide bond of the natural ligand with the corresponding linker of each analog. The geometry of each structure was optimized using Macromodel v9.9, and conformational sampling was performed employing the Macrocycle Conformational Sampling option of Macromodel v9.9 with the OPLS 2005 force field. The distance-dependent dielectric was used with enhanced sampling mode. For each structure conformers above 5.0 kcal/mol of the identified global minimum were excluded, as were conformers that were less than 1.5 Å RMSD of a previously sampled conformer. The large scale low-mode method was applied to 10000 simulation cycles.
To further reduce the number of conformers of each compound sampled by Macromodel, the backbone atoms of its conformers were superimposed and clustering was performed using the trjconv and g_cluster modules of GROMACS, respectively. The centroid of each cluster was selected. To analyze the conformational effects of each linker, a pairwise RMSD distance matrix was computed the centroids of all the compounds using a python script in Chimera v1.62.
3.10.6. Isothermal titration calorimetry measurements
Calorimetric measurements were recorded using an iTC200 calorimeter. In brief, a solution of 40 μL of the peptide ligand, at a concentration 10-fold greater than that of ASF or fetuin, was titrated in aliquots of 2 μL into the calorimetric cell at 1000 rpm, containing 203 μL of ASF or fetuin. Both, peptide ligand and the glycoproteins were dialyzed and prepared in exactly the same buffer containing 20 mM HEPES, pH 7.0. Injections were performed every 180 s at 25°C. A titration of each peptide in the sample cell containing only buffer was subtracted from the actual binding experiment before data analysis. The thermodynamic analysis was performed using the
MicroCal analysis software (Origin 7.0).
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3.10.7. Fluorescently-labeled in vitro lectin cell-based assays
Cell lines were grown in their specified media, as recommended by ATCC in tissue flasks to approximately 80% confluency, gently trypsinized with Accutase, washed with PBS and incubated in the 4% paraformaldehyde- Dulbecco’s PBS solution to fix the cells on 96-well plates in their recommended cell/well concentration. The wells were then washed with PBS, incubated with 3% BSA in PBS buffer for 30 min (blocking), followed by Dulbecco’s PBS wash and incubated with fluorescently-labeled lectins or peptides at varied concentrations for 90 min at
25 C with gentle mixing on a shaker platform, then washed with Dulbecco’s PBS, mounted and examined and pictures were taken with a fluorescent microscope (Olympus, Waltham, MA) and camera (Photometrics, Tucson, AZ), then fluorescence signal was monitored using Synergy H4 microplate reader (Biotek).
3.10.8. Fluorescently-labeled in vitro inhibition competitive cell-based assay
The inhibition of binding of OL-FITC was determined in the presence of unlabeled native
OL ranging in concentration from 1 × 10−12 M to 1 × 10−3 M. Serial dilutions (1:10) of unlabeled native OL was prepared in Dulbecco’s PBS buffer, and the appropriate concentration was added
(5 µL) to each well, followed by 90 µL of Dulbecco’s assay buffer, followed by 5 µL of the fluorescent ligand (60 μg/mL final concentration). Reaction mixtures were incubated at room temperature in the dark for over 2.5 h with gentle mixing on a shaker platform, then fluorescence was measured as described above. The IC50 values were analyzed by non-linear regression analysis by GraphPad Prism v4.03.
3.10.9. Cell viability assay
Time-course viability of peptides was determined after 48h and 72h exposure, and assessed using Cell Titer-Glo Luminescent Cell Viability Assay (Promega), a homogeneous method of determining the number of viable cells in culture based on quantitation of the ATP present using the Cell Titer Glo colorimetric assay. Assays were set up in flat-bottom polystyrene
96-well plates with 10,000 BJ (ATCC® CRL-2522™) cells per well grown in EMEM containing 10%
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FBS, and 5% penicillin/streptomycin (v/v). After an overnight incubation at 37°C under a humidified atmosphere with 5% CO2, media were removed, and fresh media with 2% FBS containing peptides in a concentration range of 60-2000 μg/mL were added. Plates were again incubated at 37°C under a humidified atmosphere with 5% CO2. Doxorubicin at 10 μM and 20%
DMSO were used as positive controls for monitoring cell viability. After incubation for 48 and 72 h, respectively, media were removed, and 100 μL PBS buffer was added, followed by 100 μL of Cell
Titer Glo® Reagent. Plates were incubated for further 10 m at room temperature (protected from light), before luminescence readout. Viability was expressed as a percentage relative to wells containing media only.
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CHAPTER 4
DELIVERY OF ODORRANALECTIN (OL) TO THE BRAIN
VIA INTRANASAL ROUTE
4.1. Overview
In 2008, Neuroinsights reported that the worldwide economic burden caused by central nervous system (CNS) diseases has reached over $2 trillion a year, and it is likely that this burden will continue to rise with the increasingly ageing population.482 The blood-brain barrier
(BBB) and the blood-cerebrospinal fluid barrier (BCSFB) represent the two major obstacles for delivery of therapeutics to the CNS.483-485 More than 98% of all small-molecules do not cross the
BBB, while no large-molecule drugs, including peptides, recombinant proteins, and monoclonal antibodies, cross the barrier.282,283,486,487 In fact, of the 7000 molecules in the Comprehensive
Medical Chemistry (CMC) database, less than 5% are active in the CNS.488 Nearly all of the larger drugs and most of the smaller drugs are not able to reach the brain in high enough concentrations to exert an effect.183 This is mainly due to the BBB, a highly-dynamic neuroprotective barrier, constituted by the endothelial cells of the capillaries in the brain. In short,
BBB function’s results from 3 layers of protection: a physical barrier (tight junctions prevent para- cellular transport), a transport barrier (specific transport mechanisms for in- and efflux, controlling trans-cellular transport) and a metabolic barrier (metabolizing enzymes prevent trans-cellular transport).489,490 Diseases of the CNS such as schizophrenia, meningitis, migraine, Parkinson’s and Alzheimer’s disease, along with other neurological disorders,491 such as addiction, require delivery of the drug to the brain for effective treatment. Currently, successful drugs can be divided into two classes: a) traditionally small-molecule drugs with typical MW of <500 Da with good oral bioavailability, and b) much larger biologics typically >5000 Da that are not orally bioavailable.179,180 These two classes are separated by a significant gap in MW that has not been
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exploited extensively by industry. Peptides represent a class of molecules that have the specificity and potency of larger biologics, but are smaller in size and more synthetically accessible, thus potentially combining some of the advantages of proteins with those of small- molecules.179,180 However, conventional drug delivery methods show to be inefficient in delivering a number of therapeutic agents to the brain, especially hydrophilic and large MW drugs, such as peptides and proteins.485,492,493 Both the BBB and blood-cerebrospinal fluid (CSF) barrier restrict the transport of these therapeutic agents from systemic circulation into the CNS.282,283,486,487
Therefore, it is of the utmost importance to search for novel drug delivery strategies that can effectively deliver peptide-based therapeutics into the CNS.
4.2. Direct nose-to-brain drug delivery via intranasal administration
It has been shown in literature from animal and human studies that intranasal administration may enable drugs to directly enter the brain by bypassing the BBB (Figure
30).485,494-499
Figure 30. Pathways for brain delivery after intranasal administration485.
This delivery route involves the olfactory or trigeminal nerve systems which initiate in the brain and terminate in the nasal cavity at the olfactory neuroepithelium or respiratory epithelium
(Figure 31).492,495,500,501 Therefore, better targeting action can be achieved due to direct transport of a drug from the submucosal space of the nose into the cerebrospinal fluid compartment of the
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brain, avoiding systemic circulation of the drug, and reducing the risk of systemic side effects, as well as hepatic/renal clearing (Table 4).484,502,503
Figure 31. A) Anatomy of the nose and brain; B) Potential transport routes for substances into the brain.484,499
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Table 4. Key benefits offered by nasal drug delivery systems.484,496
Key benefits Delivery system Nasal Oral Parenteral Higher drug levels Yes No Yes Rapid onset Yes No Yes Pain at the site of No No Yes administration Self-administration Yes Yes No BBB bypass Yes No No Patient compliance High High Low Hepatic first pass metabolism No Yes No Drug degradation Low High No
Large surface area, porous endothelial membrane, high total blood flow, the avoidance of first-pass metabolism, and ready accessibility are a few of the major reasons for drug delivery across nasal mucosa.484 This process is initiated by absorption of the drug and its passage through the mucus. Subsequent to this, there are several mechanisms for absorption through the mucosa: 1) passive diffusion, in which gaseous molecules such as O2, CO2 and small lipid- soluble compounds (generally 300-500 Da) can diffuse passively to cross the BBB; 2) active transport, which can be divided into three types: carrier-mediated transport (CMT), absorptive- mediated transcytosis (AMT), and receptor-mediated transcytosis (RMT) (Figure 32).488,504 Active transport is usually the mechanism by which highly specific compounds, which can be hydrophilic and large, enter the CNS. While this delivery route has been successfully demonstrated in animal models485, its clinical use is less clear mainly due to the relatively diminutive presence and distribution of the human olfactory mucosa.505 However, confirmation of the permeability of nasal mucosa to very large and polar molecules501,506 suggests the potential for a novel alternative delivery method. Direct nose-to-brain drug delivery therefore offers a practical, convenient, non- invasive, reliable, safe route and rapid method to deliver faster and higher levels of therapeutic agents into the CNS (Table 5).484
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Figure 32. Pathways across the blood-brain barrier (BBB). A) the paracellular pathway; B) the transcellular pathway; C) receptor-mediated and/or absorptive-mediated transcytosis; D) carrier- mediated transport.475,484
Table 5. Advantages and limitations of nasal drug delivery.484,496
Advantages Limitations a) Drug degradation in the GI a) Rapid elimination of drug substances tract is avoided from nasal cavity due to mucocilliary b) Hepatic first pass metabolism clearance is avoided b) Nasal cavity provides smaller absorption c) Rapid drug absorption and surface area as compared to GI tract quick onset of action can be c) Absorption enhancers used in achieved formulation may create mucosal toxicity d) Excellent route for systemic d) Mechanical loss of the dosage form could delivery of drugs that show occur due to improper technique of poor absorption though oral administration route e) Low bioavailability may result from e) Better patient compliance enzymatic degradation and metabolism f) Shows excellent bioavailability at mucosal surface for small and low MW drugs
The quantities of drug administered nasally that have been shown to be transported directly from nose-to-brain are very low, typically less than 0.1%.506 Drug hydrophobicity, MW and degree of ionization affect the drug transport into the CNS after intranasal administration.485,493,507
In order to improve intranasal drug delivery to the brain, two main approaches have been utilized:
(a) modification of permeability of nasal membrane by employment of absorption enhancers, such as surfactants, bile salts, fatty acids and polymeric enhancers,508,509 and (b) use of nanoparticle
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(NP) systems that can carry drugs across the mucosal barrier and protect drugs from degradation in the nasal cavity.502,506,510-512 However, these approaches are not without shortcomings. In the case of absorption-enhancing molecules, local or systemic intolerance after inhalation and membrane damage observed for many enhancers represent major limitations.501,508 Suboptimal delivery due to limited transmucosal transfer of NPs, slow drug release (limits bioavailability), and short resident time in the nasal cavity (due to mucocilliary clearance) are limitations typically associated with NPs.513-516 In addition, it is unclear whether the drug is being released from the nanoparticle system in the nasal cavity and transported to CNS, or if the NP is transported along the olfactory and/or trigeminal nerve pathways into the CNS, where the drug is released.485,510
The challenge now is to improve the transfer efficiency of the drug from the olfactory epithelium to the brain, in order to safely, predictably and successfully reach therapeutically relevant levels in the target regions of the brain.
4.3. Exploitation of fucose for intranasal drug delivery
It has been shown that OL specifically bind to L-fucose. This particular sugar is widely distributed on the olfactory epithelium of nasal mucosa, suggesting a possibility for extending its residence time in the nasal cavity, thereby allowing its increased adsorption.517-523 Secondly, OL has been shown to exhibit extremely low toxicity and immunogenicity in mice, and it was stable in mice plasma for at least 5 h.373 These characteristics make OL a particularly attractive structure for developing novel carrier systems for nose-to-brain drug delivery of therapeutics, bypassing the
BBB, providing a noninvasive and effective route for the treatment of CNS disorders. Fucose has been shown to have greater expression on olfactory mucosa than on respiratory mucosa.
Recently, several groups have conjugated OL and other lectins475,490 to NPs to increase brain targeting following intranasal administration,511,524-526 However, the native OL peptide itself has not been detected in the brain.
This study is focused on the intranasal delivery of native OL for direct nose-to-brain potential drug delivery. Confirmation that the native OL peptide was detected in brain mice samples by mass spectrometry. Overall, the results of this study indicate that the native OL can
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be delivered via the nasal route to the mouse brain. Furthermore, this study shows the possibility of how a novel strategy for improved intranasal delivery can be exploited for pharmaceutically relevant bioactive peptides to the brain based on exploitation of a high abundance of L-fucose on olfactory mucosa for extending the residence time of bioactive peptide in the nasal cavity.
These preliminary data demonstrated the feasibility of the molecular grafting approach for the design of novel platforms for direct nose-to-brain delivery of therapeutic peptides and may have broad implications in the development of novel drugs and delivery carriers for brain targeting.
4.4. Solid-phase synthesis
We have successfully synthesized the native OL natural product (Scheme 3), and a control cyclic peptide composed of a randomly permutated OL sequence (SC-OL), using standard
Fmoc-solid phase approach412,413 and on-resin disulfide bridge formation by iodine oxidation. In addition, to confirm that the Lys5, Cys6, Phe7, Cys16, and Thr17 residues in the OL scaffold are crucial for fucose binding, we have prepared a control peptide composed of a randomly scrambled OL sequence (SC-OL). All peptides were purified by RP-HPLC and characterized by
MALDI-TOF MS, analytical RP-HPLC, and CD spectroscopy.
4.4.1. Synthesis of native odorranalectin (OL)
We have developed an efficient Fmoc-solid phase approach for the synthesis of native
OL as previously described in section 3.4.1. ( Scheme 3).
4.4.2. Synthesis of the randomized scrambled analog (SC-OL)
A randomized cyclic scrambled peptide based on the parent OL peptide (SC-OL) with the following sequence (RVFSL-cyclo[CNATYPYKGAC]P) was synthesized as previously described for the native OL peptide (see section 3.4.1.).
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4.5. Thermodynamic assessment study
4.5.1. Assessment of binding interaction of native OL and its randomly scrambled (SC-OL) analog with fucosylated-glycoproteins
To assess whether the binding specificity of the native OL peptide had any effect on the binding capability of the peptide to fucosylated-glycoproteins, we chose to study the binding profiles of native OL and its randomly scrambled analog SC-OL control peptide, with asialofetuin
(ASF) as the glycan binding partner, since it is considered a model for fucose-containing glycoproteins. The binding affinities of the native OL and its randomly scrambled analog SC-OL towards ASF were assessed by ITC. As expected, affinity of the randomized scrambled control peptide (SC-OL) toward ASF (Kd = 758 μM; Figure 33) is significantly lower compared to OL (Kd =
63 μM; Figure 22 A), indicating that these residues are not amenable to modification.
Figure 33. Isothermal titration calorimetry (ITC) data for randomly scrambled OL peptide analog (SC-OL) (3 mM) with ASF (250 uM). The top panel shows the experimental ITC data and bottom panel shows a fit to one-site model of the binding data using MicroCal analysis software (Origin 7.0). The best values for the stoichiometry (n), binding affinity (Ka), dissociation constant (Kd), enthalpy (ΔH), and change in entropy with respect to temperature (TΔS) are shown in the graph below.
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4.6. In vivo intranasal administration study
4.6.1. In vivo intranasal administration, tissue collection and processing of native OL for
detection by LC-MS/MS
To examine the nose-to-brain delivery in vivo of native OL, the selected peptide in saline solution was administered intranasally to mice (in duplicates) at the openings of nostrils (240 μg,
10 μL each nostril; 480 μg/mouse final concentration) to conscious mice fixed by hand in supine position using a micropipette, and mice were euthanized at various time points (30, 60, 120 and
240 min) post-administration and blood removed by cardiac puncture, followed by cardiac perfusion and removal of olfactory nerves and perfused brain, homogenized and extracted for the compound using established protocols (see below). Extracted brain and nerve tissue samples were isolated, homogenized and extracted using an organic solvent, then processed and analyzed in qualitative and quantitative assays using LC-MS/MS for the presence of the parent peptide.
LC-MS/MS analytical methods specific to the selected individual OL analogs were adapted as previously described.527,528 The quantitative analysis was carried out using appropriate internal standards (e.g. WssF tetrapeptide) to eliminate processing errors.527,529
Figure 34. Detection of OL in mouse nose, brain and olfactory nerve based on average peak ratio given by the m/z of parent and fragment ion and the IS in LC-MS/MS.
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Native OL was detected in the mice nose and brain processed samples ranging from 30 min to 4 h after intranasal administration of peptide at highest peptide concentration (480
μg/mouse) and it was eliminated from the brain in about 240 min (Figure 34). It is worth mentioning that native OL was not detected in the olfactory nerve. This is probably due to the small tissue sample, characteristic of the olfactory nerve. The level of OL in the mouse brain at 30 min time intervals parallels those in the mouse nose. Further optimization trials with tissue processing of the olfactory nerve will allow detection of the peptide. In addition, native OL did not show any toxicity in the in vivo studies and mice reactions upon administration were normal.
4.7. Discussion and conclusions
Despite the enormous potential market for the pharmaceutical industry, the targeting of drugs and diagnostic agents to the CNS is challenged by the presence of the BBB.488 Given this scenario, it is clear that there is an urgent need to develop efficient delivery vectors (BBB- shuttles) able to transport different types of cargo across the BBB.488 Thus, since the last few decades, nasal route has attracted a wide attention of researchers as a convenient, non-invasive, reliable, and safe route to achieve faster and higher levels of drug in the brain. This clearly exemplifies the potential of nasal mucosa as an administration route for targeting the CNS, in particular, the brain.484
More specifically, in trans-nasal drug delivery, once the molecule crosses the nasal epithelial barrier and enters the subcutaneous space of the nose, it can diffuse across the arachnoid membrane and enter the CSF compartment of the olfactory region. Small lipophilic molecules not only cross the BBB via passive diffusion but also cross the nasal epithelial barrier and the arachnoid membrane. In situations involving the administration of a drug that is hydrophilic or that has a MW higher than 400 Da, the disruption of the epithelial barrier may be required in order to achieve transport by means of active transport.488
Recent years witnessed several key advances in the development of peptides as therapeutic agents and drug carrier for brain disorders. Many large peptides cross the BBB by passive diffusion, such as diketopiperazines (DKPs) transport baicalin and highly N-methylated
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488 phenylalanine-rich peptides transport L-dopa. In addition to passive diffusion, absorptive- mediated transcytosis (AMT) is another mechanisms by which cell-penetrating peptides (CPPs) and other cationic compounds overcome the BBB. This process begins with the interaction of the cationic residues of a CPP (TAT, penetratin, pegelin and oligoarginine) with the negative charges on the plasma membrane surface are (e.g. proteoglycans). This interaction triggers endocytosis, which can lead to transcytosis.488 Lastly, the receptor-mediated transcytosis (RMT) is by far the most promising mechanisms by which peptides transport cargos across the BBB. In general,
RMT occurs in three steps: receptor-mediated endocytosis of the compound at the luminal
(blood) side, movement through the endothelial cytoplasm, and exocytosis of the compound at the albuminal (brain) side of the capillary endothelium.488,491 Therefore, it will be most interesting to develop a universal BBB-shuttle with the capacity to transport any type of cargo into the CNS, and moreover, in a highly selective and efficient way. As an ideal requirement, this universal shuttle should be safe for human applications and easy to produce. The most convenient mechanism that fulfills these requirements is RMT. Peptides offer an interesting alternative to the use of antibodies or proteins as BBB-shuttles, because they offer the following advantages: a) they have relatively small MW; b) they can be synthesized easily and relatively inexpensively; c) they are degraded in vivo to naturally occurring compounds.488
The experiments of this study clearly show that native OL can be delivered directly to the brain via intranasal administration. To confirm that the Lys5, Cys6, Phe7, Cys16, and Thr17 residues in the OL scaffold are crucial for fucose binding, our control peptide SC-OL has significantly lower binding affinity towards ASF when compared to OL, indicating that these residues are not amenable to modification.
While there is still room that allows for optimization for the detection and quantitation of native OL in mice, we can rest assured that in vivo mice studies (Figure 34) show fast intranasal delivery of native OL to mouse brain in amounts detectable by mass spectrometry, thus offering a novel brain drug delivery system for the treatment of CNS disorders, and can further be modified to aid in increasing drug delivery by acting as a bio-recognitive ligand across the BBB (direct nose-to-brain delivery), or used as a drug delivery vehicle for theranostic purposes.
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4.8. Materials and methods
4.8.1. Chemicals and instrumentation
Tentagel S RAM resin was obtained from Advanced Chemtech (Louisville, KY). Fmoc- protected amino acids, and coupling reagents (HOBt, HBTU, PyBOP) were purchased from
Chem-Impex (Wood Dale, IL) or Novabiochem. DIC was purchased from Acros Organics
(Thermo Fisher Scientific, Waltham, MA). Kaiser test was purchased from AnaSpec (Fremont,
CA). All solvents were purchased from Fisher Scientific (Atlanta, GA) or Sigma–Aldrich, and were high-performance liquid chromatography (HPLC) grade. ASF and iodine were purchased from
Sigma-Aldrich (St. Louis, MO).
Linear peptidyl-resin precursors were synthesized on a PS3 automated peptide synthesizer (Protein Technologies Inc., Tucson, AZ). Mass spectrometry was performed on
MALDI-TOF Vogager-DE™ STR (Applied Biosystems, Foster City, CA) in reflector-mode using α- cyano-4-hydroxycinnamic acid as a matrix and in positive mode. Analytical RP-HPLC analyses and peptide purifications were performed on 1260 Infinity (Agilent Technologies, Santa Clara, CA,
USA) liquid chromatography systems equipped with a UV/Vis detector. For analytical RP-HPLC
-1 analysis, a C18 monomeric column (Grace Vydac, 250 x 4.6 mm, 5 µm, 120 Å), 1 mL.min flow rate, and elution method with a linear gradient of 2→100% B over 45 minutes, where A is 0.1%
TFA in H2O, and B is 0.08% TFA in CH3CN was used. For peptide purification, a preparative C18 monomeric column (Grace Vydac, 250 x 22 mm, 10 mm, 120 Å) was used. Elution method was identical to the analytical method except for the flow rate, which was 20 mL.min-1. CD spectra were recorded on a JASCO 810 spectropolarimeter (Easton, MD) using a quartz cell of 0.1 mm optical path length. Spectra were measured over a wavelength range of 180–250 nm with an instrument scanning speed 200 nm.min-1 and a response time of 1 s. The concentrations of peptides were 0.1–0.2 mM.
Brain, nerve, and nose homogenate samples were done with a Power Gen 125 homogenizer (Thermo Fisher Scientific, Waltham, MA).
105
4.8.2. Animals and reagents
The in vivo experiments were carried out using male C57BL/6J mice (The Jackson
Laboratory, Bar Harbor, ME) of ages 7-10 weeks old. C57BL/6J mice are used as they are established subjects for studies of both drug pharmacokinetics530 and brain-penetrant properties.527,528 Mice were kept in groups of four in a temperature-controlled room with 12-hour light/dark cycle. Food and water was available ad libitum until the time of the experiment. All mice were housed, tested, and cared for in accordance with the 2002 National Institutes of
HealthGuide for the Care and Use of Laboratory Animalsand as approved by the Institutional
Animal Care and Use Committee.
4.8.3. General procedure for peptide synthesis and purification
All linear peptidyl-resin precursors for native OL, SC-OL and DADLE-OL were synthesized by Fmoc-SPPS on Rink amide MBHA resin (substitution 0.66 mmol/g, 0.25 mmol scale) and Tentagel S RAM resin (substitution 0.25 mmol/g, 0.25 mmol scale), respectively, using automated peptide synthesizer when indicated (see section 4.4). Amino-acid couplings were done by using double couplings with six-fold excess of amino acids and coupling reagents
(HOBt/HBTU) in 0.4M NMM in DMF. Fmoc-deprotection cycles were carried out using 20% piperidine in DMF solution.
Linear peptidyl native OL and SC-OL peptides were synthesized on an automated peptide synthesizer. Fmoc was used for Nα-protection with the exception of the last amino-acid incorporated, Boc-Tyr(tBu)-OH, and the following groups were chosen for protecting side-chain functionalities: Boc for Lys; tBu for Thr, Ser, and Tyr;; Pbf for Arg; Trt for Asn and Cys. After assembly of the complete linear peptide sequence, solid-phase cyclization was achieved by disulfide bridge formation with subsequent removal of Trt group and final cyclization with iodine
(10 eq) and 2% anisole in NMP( 2x30 min).414
106
4.8.4. Intranasal administration of native OL to mice
The in vivo intranasal administration studies were performed by Dr. Jay McLaughlin’s group at Torrey Pines Institute for Molecular Studies, Port St. Lucie, FL.
We adapted the procedure used by earlier groups for use in mice.524-526 A native OL working stock of 40 mg/mL was made up with saline (0.9%) as vehicle. It is worth mentioning that slight turbidity was observed for this high concentration of peptide solution. It should be noted that all mice were male C57BL/6J (The Jackson Laboratory, Bar Harbor, ME) of ages 7-10 weeks old, weighing approximately 23-26 g. Each mouse was anesthetized in a chamber with 0.4% isoflurane until the loss of consciousness and righting reflex was observed. Mice were then removed, and OL working stock was applied to each nostril (6 μL/nostril) using a p20 pipette with a 20 μL tip, for a total of 12μL per mouse. For the native OL, this works out to be 60 μg of compound administered to each mouse. Care was taken to insert the tip just into the nostril, and to infuse the fluid over a 3 s period. A very small (~0.1-0.2 μL) amount of fluid was sometimes seen to run down the centerline of the nose into the mouth; this was observed in perhaps 2 or 3 mice (out of 10). After infusing sample into both nostrils, mice were placed back in the anesthetic chamber for 90 s in a supine position, to facilitate absorbance of the treatment. The fluid was generally inhaled into the nose without consequence. No sneezing was observed, and the animals were noted to breathe comfortably and normally. Mice were then placed in their home cages, where they awoke within a min. Reactions upon waking were generally normal (brief hyperactivity, modest uncoordinated locomotion, and exploratory behavior). Roughly most of the animals rubbed their snouts, but no mice were observed to sneeze or attempt to expel the treatment. Breathing and activity appeared normal thereafter. Mice were later euthanized at the various time points.
4.8.5. Tissue collection and processing for native OL detection
Mice were further transcardially perfused with ice-cold Dulbecco’s PBS-buffered saline to remove traces of blood from the cerebrovasculature. Two additional mice received saline as a control, and two untreated mice were also being harvested as blanks. The nasal tissue, olfactory
107
nerve, and unperfused brain from pairs of mice at 30, 60, 120 and 240 m were harvested for tissue processing. Tissue samples were removed and placed on wet ice immediately until processed. The brains were weighed and homogenized in 250 mL of ice-cold Dulbecco’s PBS- buffered saline using an ergonomic Power Gen 125 homogenizer (Thermo Fisher Scientific,
Waltham, MA), and vigorously shaken on a vortex-mixer. Immediately after the first homogenization, proteins were be precipitated by addition of ice-cold ACN (1 mL) containing andthe WsSF internal standard (IS) tetrapeptide and further homogenized. The homogenates were centrifuged at 10,000 rpm at 4°C for 5 minutes to form a pellet. The entire quantity of supernatant was collected and dried under vacuum as before. The residues were re-suspended in 5% acetonitrile/water and centrifuged again at 13,000 rpm for 5 m at 4°C. The supernatants
(100 μL) were then injected (10 μL) onto the HPLC column for the LC-MS/MS analysis.
4.8.6. Native OL detection by LC-MS/MS mass spectrometry
The developed method was validated for detection purposes only. Samples were analyzed in reverse phase MRM mode on a Shimazdu LC-20A prominence LC system connected to Absciex 3200 Q Trap MS/MS on Phenomenex Luna C18 5μm 250 x 4.6mm column. Detection of native OL was estimated by calculating the average peak area ratio of the analyte (OL) to the
IS. Data comparing cyclic peptides quantities in brain samples quantified by LC-MS/MS over time will be analyzed by one-way ANOVA, with significant effects further analyzed using Tukey’s multiple comparison post hoc test as previously described.527 Effects will be considered significant when P<0.05. All effects will be expressed as mean ± SEM.
108
APPENDICES
109
APPENDIX A
RP-HPLC chromatograms and MALDI-TOF MS spectra of synthetic native OL and its analogs
Voyager Spec #1=>TR[BP = 1886.6, 30720] 1886.6637 100 3.1E+4 90
80
70
60
50 1888.7112
% Intensity % 40 30 1908.6532 20 1924.6418 10 1151.8237 1453.1008 1693.7168 2299.3577 2644.3486 0 1000 1400 1800 2200 2600 3000 Mass (m/z)
Figure 35. RP-HPLC chromatogram trace (above) and MALDI-TOF spectrum (below) of native OL. RP-HPLC chromatogram signal wavelengths (DAD1): A) at 300nm, B) at 254 nm and C) at 214 nm.
110
Voyager Spec #1[BP = 1867.0, 12780] 1866.9314 100 1.3E+4 90 80 70 60 50
40 %Intensity 30 20 1870.1740 10 0 0 999.0 1399.4 1799.8 2200.2 2600.6 3001.0 Mass (m/z)
Figure 36. RP-HPLC chromatogram trace (above) and MALDI-TOF spectrum (below) of OLA3. RP-HPLC chromatogram signal wavelengths (DAD1): A) at 300nm, B) at 254 nm and C) at 214 nm.
111
Voyager Spec #1=>BC=>NF0.7=>NF0.9=>TR[BP = 1864.4, 62802] 1864.3788 100 6.3E+4 90 80 70 60 50
40 %Intensity 30 1867.7367 20 1457.4156 1902.0028 10 1433.4558 0 0 1000 1400 1800 2200 2600 3000 Mass (m/z)
Figure 37. RP-HPLC chromatogram trace (above) and MALDI-TOF spectrum (below) of OLA4. RP-HPLC chromatogram signal wavelengths (DAD1): A) at 300nm, B) at 254 nm and C) at 214 nm.
112
Voyager Spec #1=>TR=>TR[BP = 1890.4, 56348] 1890.4448 100 5.6E+4 90
80
70
60 50 1892.3577
% Intensity % 40
30
20 1912.4270 10 1308.6191 2213.9951 2486.2043 2768.9717 0 1000 1400 1800 2200 2600 3000 Mass (m/z)
Figure 38. RP-HPLC chromatogram trace (above) and MADI-TOF spectrum (below) of OL linear. RP-HPLC chromatogram signal wavelengths (DAD1): A) at 300nm, B) at 254 nm and C) at 214 nm.
113
Voyager Spec #1=>BC=>NF0.7=>NF0.7=>TR[BP = 2566.6, 33355] 2566.5898 100 3.3E+4 90 80 70 60 50
40 %Intensity 30
20 2570.4191 10 1283.6950 2604.5233 0 0 1000 1600 2200 2800 3400 4000 Mass (m/z)
Figure 39. RP-HPLC chromatogram trace (above) and MADI-TOF spectrum (below) of OL-FAM. RP-HPLC chromatogram signal wavelengths (DAD1): A) at 300nm, B) at 254 nm and C) at 214 nm.
114
Voyager Spec #1=>BC=>NF0.7=>TR[BP = 2544.7, 1281] 2544.6702 100 1281.1 90 80 70 60 50
40 %Intensity 30 20 2566.5114 10 2584.2854 3060.2465 0 0 1000 1600 2200 2800 3400 4000 Mass (m/z)
Figure 40. RP-HPLC chromatogram trace (above) and MADI-TOF spectrum (below) of OLA3- FAM. RP-HPLC chromatogram signal wavelengths (DAD1): A) at 300nm, B) at 254 nm and C) at 214 nm.
115
Voyager Spec #1=>BC=>NF0.7=>NF0.7=>TR[BP = 2566.6, 33355] 2566.5898 100 3.3E+4 90 80 70 60 50
40 %Intensity 30
20 2570.4191 10 1283.6950 2604.5233 0 0 1000 1600 2200 2800 3400 4000 Mass (m/z)
Figure 41. RP-HPLC chromatogram trace (above) and MADI-TOF spectrum (below) of OLA4- FAM. RP-HPLC chromatogram signal wavelengths (DAD1): A) at 300nm, B) at 254 nm and C) at 214 nm.
116
Voyager Spec #1=>BC=>NF0.7[BP = 1888.7, 15192] 1888.7023 100 1.5E+4 90 80 70 60 50
40 1891.7334 %Intensity 30 20 1910.7218 10 1788.4753 0 0 999.0 1399.4 1799.8 2200.2 2600.6 3001.0 Mass (m/z)
Figure 42. RP-HPLC chromatogram trace (above) and MALDI-TOF spectrum (below) of SC-OL. RP-HPLC chromatogram signal wavelengths (DAD1): A) at 300nm, B) at 254 nm and C) at 214 nm.
117
APPENDIX B
LC chromatograms and MS spectra of mice tissue samples for OL detection.
117
Figure 43 A. OL peptide detection in nose tissue samples after 30 min intranasal administration. LC chromatogram trace. Insert: enhanced section of detected OL peptide (blue and red). (WssF tetrapeptide, IS = gray and green).
118
Figure 43 B. OL peptide detection in nose tissue samples after 30 min intranasal administration. MS/MS chromatogram using molecular reaction monitoring (MRM) mode for M+2 = 944. (WssF tetrapeptide, IS M+ = 525).
119
Figure 44 A. OL peptide detection in brain tissue samples after 30 min intranasal administration. LC chromatogram trace. Insert: enhanced section of detected OL peptide (blue and red). (WssF tetrapeptide, IS = gray and green).
120
Figure44 B. OL peptide detection in brain tissue samples after 30 min intranasal administration. MS/MS chromatogram using molecular reaction monitoring (MRM) mode for M+2 = 944. (WssF tetrapeptide, IS M+ = 525).
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